#been looking through the python math library today

[comparatorclock]

Lingual question

Have you ever tried to think of a word you think you should know, but then settle on an alternate word that you definitely know, but doesn't sound quite right?

[classbazaar]

Explore Free Online Courses: Learn New Skills from Home

In today's fast-paced digital world, learning has never been more accessible. With the rise of free online courses, anyone with an internet connection can now acquire new skills, deepen their knowledge, and even change their career path—all without spending a dime. Whether you're looking to improve your professional expertise, explore a new hobby, or simply quench your thirst for knowledge, free online courses are a powerful tool for self-improvement.

Why Choose Free Online Courses?

Free online courses offer an unparalleled opportunity for individuals to learn without the financial burden of traditional education. They are ideal for:

Career Advancement: Many free courses are designed by industry experts and prestigious institutions, offering skills that are directly applicable to your career.

Personal Development: From language learning to creative arts, you can explore a wide range of subjects that interest you.

Flexibility: Learn at your own pace, on your own schedule, and from the comfort of your home.

Accessibility: With just a device and internet connection, quality education is available to everyone, regardless of geographic location or financial status.

Popular Platforms Offering Free Online Courses

Several online platforms provide a vast selection of free courses across various disciplines. Some of the most popular platforms include:

Coursera: Partnering with top universities and organizations, Coursera offers free courses in fields such as business, technology, and humanities.

edX: Founded by Harvard and MIT, edX provides access to high-quality courses from leading institutions worldwide.

Udemy: Udemy's extensive library includes thousands of free courses on topics ranging from programming to personal development.

Khan Academy: Best known for its focus on K-12 education, Khan Academy also offers free courses in subjects like math, science, and economics.

How to Get the Most Out of Free Online Courses

To maximize the benefits of free online courses, it's essential to approach them with the right mindset and strategies. Here are some tips to help you succeed:

Set Clear Goals: Before starting a course, determine what you want to achieve. Whether it's mastering a new skill or gaining a certificate, having a clear goal will keep you motivated.

Create a Study Schedule: Allocate specific times during your week to study. Consistency is key to making progress.

Engage Actively: Take notes, participate in discussion forums, and complete assignments to reinforce your learning.

Practice Regularly: Apply what you've learned in real-life scenarios or through practice exercises to solidify your understanding.

Stay Committed: Free courses often require self-discipline. Stay committed to your learning journey, even when it gets challenging.

Top Categories of Free Online Courses

Free online courses are available in virtually every subject imaginable. Some of the top categories include:

1. Technology and Programming

In the ever-evolving tech world, staying updated with the latest skills is crucial. Free courses in this category cover everything from coding languages like Python and Java to data science, cybersecurity, and artificial intelligence.

2. Business and Management

For aspiring entrepreneurs or those looking to climb the corporate ladder, free courses in business strategy, leadership, marketing, and project management are invaluable.

3. Personal Development and Wellness

This category includes courses on mindfulness, mental health, time management, and more, helping you lead a balanced and fulfilling life.

4. Creative Arts

Explore your artistic side with free courses in photography, writing, graphic design, music, and other creative fields.

5. Languages

Learning a new language opens doors to new cultures and opportunities. Free language courses are available for everything from Spanish and French to less commonly taught languages like Korean or Swahili.

Benefits of Free Online Courses

Free online courses come with numerous benefits that make them an attractive option for learners of all ages:

Cost-Efficiency: As the name suggests, these courses are free, making education accessible to everyone, regardless of their financial situation.

Diverse Learning Opportunities: With courses available in a wide range of subjects, learners can explore new interests or deepen their expertise in specific areas.

Certificates of Completion: Many platforms offer certificates for free courses, which can be a valuable addition to your resume or LinkedIn profile.

Global Community: Online courses connect you with learners from around the world, providing a rich, multicultural learning experience.

Challenges of Free Online Courses

While free online courses offer many advantages, there are also some challenges to consider:

Lack of Structure: Without a set schedule or deadlines, it can be easy to procrastinate or lose focus.

Limited Interaction: Free courses may not offer the same level of interaction with instructors or peers as paid courses or traditional classrooms.

Certificate Fees: While the course content is free, some platforms may charge a fee for official certificates.

How to Choose the Right Free Online Course

Selecting the right course can be overwhelming, given the vast number of options available. Here’s how to make an informed decision:

Research the Course: Look for reviews, ratings, and testimonials from other learners.

Check the Syllabus: Ensure the course content aligns with your learning goals.

Assess the Instructor’s Credentials: Opt for courses taught by experienced professionals or institutions.

Consider the Course Length: Choose a course that fits your schedule, whether you prefer a short, intensive course or a more extended program.

Start Your Learning Journey Today

The world of free online courses is vast and full of potential. Whether you're a student, a professional, or a lifelong learner, there's something for everyone. At Class Bazaar, we curate the best free online courses across various platforms and disciplines, making it easier for you to find the right course to match your goals.

Ready to unlock new opportunities? Explore our free online courses and start learning today!

[jeremy-ken-anderson]

God, What a Week (It's Tuesday.)

Made fudge rounds 1 and 2. Did the math, realized I can't send 12 pieces per person unless I make a 5th batch because there are 9 households on the receiving end of this. 25 pieces per batch x 4 batches means 100 pieces, so I could do 10 per person and have 10 for my own household, or I could just make a fifth batch. I'm inclined toward solutions that leave a lot of fudge in the house, because

We're talking through end-of-life for our dog Maya, who's been with us basically since we moved up here. She's a megamutt (a breed identification service that goes back 4-5 generations offered us a refund because she's composed of so many breeds they couldn't identify her) Guatemalan street dog with a lightly-blonde white coat that makes her look like a toasted marshmallow. We know that she's had a good life, and that we've given her a lot more of a life than she'd have had if we hadn't taken her off the streets down there, and that she's in near-constant pain now. But that doesn't make deciding to end the life of this little person who expresses joy at your presence any easier. The whole household is flattened by this. We have no spoons to spare.

Didn't have work today, because the client decided to put their start date off for a month. I have immense gratitude that I've stabilized enough financially to not feel like that 32 hours of work I don't have is going to be food out of my mouth, and can enjoy having those hours back to work on classes, creative projects, and (as it turns out) grieving.

Class is going well. It looks far more feasible that I can finish all my HCA classes in time than it did a few days ago, and the Python coursework is going smoothly.

I'm picking up Just Stab Me Now by Jill Bearup from the library today. I'm hoping it'll be engaging but putdownable enough that I can read it when clients are sleeping on-shift and I've gotten the household aid handled. If it's Ninth House engaging I'll have to settle for reading it at home and I'll stick with the Napoleon Bonaparte Mysteries for on-shift reading.

[superlinguo]

Linguistics Jobs: Interview with a Software Engineer

Like today’s interviewee, Brooke Lynne Weaver, I worked through my undergrad degree. While not everybody is lucky enough to be able to do both study and work, it can be a useful way to develop skills beyond those in the classroom. I now use my coffee making skills only for self-caffeination, but cafe life taught me a lot about task prioritising and staying upbeat under pressure. Brooke used her work experience to move into Software Engineering, and uses her linguistics in her approach to her work, and her everyday life. Brooke is also on Twitter (@Milayou).

What did you study at university?

My degree is in English Language (Linguistics with an emphasis on the English language) from Brigham Young University in Utah, U.S.A. Basically, when we covered morphology, syntax, phonetics, phonology, sociolinguistics etc. it mostly focused on those applications in English, with some examples and work from other world languages. I also took a couple computer science classes and worked as a web developer while in school.

What is your job?

I'm a software engineer. Right now my job title is Platform Engineer, and at my last job it was Platform Architecture Engineer. I write code based on the needs of my company, which generally involves understanding the task you need the computer to perform autonomously, and doing a bunch of Googling to remind yourself (or learn) how to tell it to do that. You run the code, look for certain things to happen, tweak the code, run it again, look for different results, tweak it again, run it again etc. The ask from the company is generally as specific as humans tend to be, which is not nearly as specific as machines tend to be; you have to be on the lookout for instructions that should be given that were never expressly asked for by the company in order for everything to run smoothly. Our stack is mostly written in Python 2.7 but we're moving to Go, and the project I just finished up has parts written in both. It's really satisfying when you've finally communicated your message properly to the machine and it behaves accordingly.

I work for Vivint.SmartHome right now, doing home automation. I help the Vivint centralized system interact with peoples' homes and phones all over North America. When someone pulls up their Vivint app on their phone, it requests data from our platform. When they want to make changes to their smart home system, it interacts with our platform. Recently I've been helping migrate our Nest integration from using the (now deprecated) Works With Nest API to the new Google Home/Assistant API (a transition Google recently made public).

How does your linguistics training help you in your job?

I like to tell myself I went into translation, just between human and machine languages rather than from one human language to another. The things I learned studying linguistics help me in less obvious ways.

Knowing how flexible semantics is and how language changes so much across time and space, I feel like I'm a much better communicator than I was when I first started college. I'm a lot more flexible in interpretations and I care a lot more about getting to the root of what a person is trying to communicate, rather than what words they chose and what those words mean to me specifically. Communication is a pretty important part of writing software, because you're almost always trying to realize the ideas of other people. Knowing how to be confident you're on the same page as the people requesting your work is critical.

Linguistics also gave me a much better understanding for how important context is. I leave comments everywhere it makes sense to in order to help future engineers understand why I did certain things, which puts them in a better position to understand what to change down the line. It's very common to come across some code written a few years back that seems to make no sense at all (or seems like a bad way to do something), and if someone left a comment explaining why they wrote it that way at that time, you can better decide whether to leave it or in what ways to change it. The comment might say "Here's the current state of affairs and we need to do this weird thing to avoid this problem" and now, several years later, that problem is irrelevant or the current state of affairs has drastically changed; you might not need to do that thing in such a weird way anymore. You can then feel more confident about making your change. Or, maybe the state of affairs has not changed or the problem still exists and still needs to be avoided; you now have really important context and that weird thing might actually look logical now, or you know how to change it while still avoiding the problem it was originally trying to avoid. As an example, earlier this year I implemented a library I wasn't very familiar with in a pretty short amount of time. I left a comment explaining that if someone else was more comfortable with the library, they should feel free to rewrite it in a more idiomatic way; I explained what parts of it I wrote somewhat poorly due to lack of time and familiarity (something like "I know you should be able to do it like A, but I couldn't figure out how to get A to work so I did B instead which isn't as good but gives an acceptable result. It's not deliberately done this way for any other reason, so if you know how to do A, please change it."). A lot of times we try to change legacy code as little as possible, for fear of unknown downstream affects, because we weren't there when it was written and don't know why it was done the way it was; I hope by leaving context comments I can help future engineers feel more comfortable keeping the codebase clean and efficient.

Do you have any advice you wish someone had given to you about linguistics/careers/university?

I have some advice I was given that I think is valuable. I had a really hard time choosing a major field of study because I was interested in almost everything. A counselor reminded me that you can still have any hobby you like, regardless of what you study at university. I was afraid that by choosing something I was cutting myself off from other things, but that's not actually true. I still love playing the piano even though I didn't go into music, and I still love math even though I didn't go into mathematics.

Also, my university offered a lot of student jobs. These were jobs that were only allowed to be worked by students, which meant the barrier to entry was fairly low. I don't know if other universities offer student on-campus jobs, but if they do, I very much recommend them. I worked student jobs the entire time I was at school, which meant I graduated with seven years of work experience. Yes, it took me seven years to get my bachelor degree, but that work experience meant I had no trouble getting jobs after (and even before) I graduated. That said, maintaining a job while going to school is an awful lot of work and it's not the right path for everyone; everyone's situation is different, this just worked out well for me.

Any other thoughts or comments?

Besides how linguistics training helps me at work, it's made me a FAR better human. I'm a reformed pedant. I was really condescending and had a bit of a superiority complex about language when I was young. I was all about correcting and fixing people and being exasperated when people wrote or said things "wrong." Studying linguistics has given me a LOT of empathy and understanding and freed me from most of my pet peeves. My perspective on language and communication is so different now. I feel free. It's a far pleasanter experience to put your energy toward really understanding and being understood by a person than on looking down on people and discrediting their thoughts because they don't know how some dude in the 19th century wanted a part of English to work that doesn't even make sense anyway. I think a lot of unnecessary conflict comes from different groups of people having different understandings of certain words, and fighting over the definition of the word rather than over the real human issue at the heart of the debate. It would be nice if we taught language a little differently in schools, so more people could be aware of how semantic drift occurs and how different people can use the same word to mean different things, and that language change is okay and actually beautiful.

Recently:

Interview with a Product Manager 

Interview with a Communications Specialist

Interview with a Learning Scientist

Interview with a Lexicographer

Interview with a Journalist

[data-patrons]

Kickstart Your Python for Data Science in NCR Career: Tips and Tricks for Success

Python for Data Science in NCR is one of the most in-demand fields in the world today. It combines mathematics, statistics, computer science, and domain expertise to extract insights and knowledge from data. With the rise of big data and machine learning, there has never been a better time to pursue a career in data science.

But getting started can be daunting. There are so many tools, languages, and techniques to learn, and the field is constantly evolving. In this article, we will provide you with tips and tricks on how to kickstart your data science career and succeed in this exciting field.

Kickstart Your Data Science Career: Tips and Tricks for Success

Get a Strong Foundation in Math and Statistics

Data science involves a lot of math and statistics, so it's essential to have a strong foundation in these subjects. If you're just starting out, consider taking courses in calculus, linear algebra, probability, and statistics. You should also familiarize yourself with basic programming concepts.

Data science involves a lot of math, so it's important to have a strong foundation in math subjects such as calculus, linear algebra, and statistics. Some tips for improving your math skills include:

Reviewing basic math concepts such as algebra, geometry, and trigonometry

Practicing with online math tutorials and exercises

Taking a course in calculus or linear algebra

Practicing with real-world data sets and applying statistical concepts to analyze the data

Statistics is another essential skill for data science, as it's used to analyze and interpret data. Some tips for improving your statistics skills include:

Taking a course in statistics or probability theory

Practicing with real-world data sets and applying statistical concepts to analyse the data

Learning how to use statistical software such as R or Python

Reading research papers and academic journals to keep up with the latest trends in statistics and data analysis

Learn a Programming Language

Python for Data science requires programming skills, so it's important to learn a programming language. Deep Python course training institute in NCR is the most popular language for data science, followed by R. Both languages have extensive libraries for data manipulation, visualization, and machine learning. Choose one language and become proficient in it.

Build a Portfolio

Building a portfolio is a great way to showcase your skills to potential employers. Start by working on personal projects, such as analyzing data sets or building machine learning models. You can also participate in online competitions, such as Kaggle, to showcase your skills and learn from others.

Network with Other Data Scientists

Networking is important in any field, and data science is no exception. Attend data science meetups, conferences, and events to meet other data scientists and learn about the latest trends and techniques. You can also join online communities, such as Reddit or Stack Overflow, to ask and answer questions and learn from others.

Keep Learning

Data science is a rapidly evolving field, so it's important to keep learning. Stay up-to-date with the latest tools, languages, and techniques by reading blogs, attending webinars, and taking courses. There are many online resources available, such as Coursera, edX, and Udacity, that offer courses in data science and related fields.

Find a Mentor

Having a mentor can be invaluable in your data science career. A mentor can provide guidance, advice, and feedback on your work. Look for mentors in your network or through online communities. You can also join mentorship programs, such as the Data Science Mentorship Program or the Women in Data Science Mentorship Program.

Apply for Internships and Entry-Level Positions

Internships and entry-level positions are a great way to gain hands-on experience in data science. Look for opportunities at companies that offer internships or entry-level positions, such as Google, Amazon, or Microsoft. You can also search for opportunities on job boards, such as Indeed or Glassdoor.

Keeping Up-to-Date

Top Python Course Training Institute in NCR is a constantly evolving field, so it's important to keep up-to-date with the latest trends and techniques. Here are some tips for staying up-to-date:

Follow data science blogs and read research papers and academic journals

Take online courses and attend webinars on new data science topics

Participate in online discussions and contribute to open-source projects

Attend data science conferences and events

Remember, building a successful data science career takes time and effort. It's important to be patient, persistent, and dedicated to learning and improving your skills. With the right mindset and the right skills, you can kickstart your data science career and achieve your goals.

FAQs

Q: Do I need a degree in data science to become a data scientist?

A: No, you don't need a degree in data science to become a data scientist. Many data scientists have degrees in fields such as computer science, math, statistics, or physics.

Q: What skills do I need to become a data scientist?

A: Some essential skills for a data scientist include programming, statistics, machine learning, data visualization, and domain expertise. It's also important to have strong problem-solving and communication skills.

Q: What kind of projects should I include in my portfolio?

A: Your portfolio should showcase your skills and interests. Some project ideas include data analysis of a real-world dataset, building a machine learning model, or creating a data visualization.

Q: How can I stay up-to-date with the latest trends in data science?

A: There are many resources available to stay up-to-date with the latest trends in data science. Some popular resources include blogs, webinars, and online courses. You can also join online communities and attend data science events.

Conclusion

Python for Data Science is a rewarding and challenging field that requires a strong foundation in math, programming, and statistics. To kickstart your data science career, you should focus on building a strong foundation in these subjects, learning a programming language, building a portfolio, networking with other data scientists, and keeping up-to-date with the latest trends and techniques.

By following these tips and tricks, you can start your data science journey and become a successful data scientist. Remember to keep learning, finding mentors, and applying for internships and entry-level positions to gain hands-on experience. Good luck on your data science journey!

[360digitmg-dataanalyticscourse]

How To Study Data Science

Here are the 10 finest data science bootcamps that will assist professionals turn out to be a profitable data scientist in 2021. It is critical that a data scientist have the ability to work with unstructured data. Unstructured data is undefined content material that does not match into database tables. Examples include movies, weblog posts, customer reviews, social media posts, video feeds, audio etc.

Career alternatives in data have exponentially grown in the recent few years. Companies are eager to seize data and derive insights from it due to the technological developments we're seeing. Accessibility of the info right now might help to reap a number of advantages organizations from it. Because of this purpose, corporations are not shying away from offering elevated data scientist salaries in India. Companies are throwing big salaries at these having expertise to tackle the positions of Data Analysts, Scientists, Engineers, and so forth. There are more than 2.3 million open jobs asking for analytics skills. This program has been strategically designed to organize college students for the analytics field by constructing a strong theoretical basis and applying it to actual-world business issues.

But Data Science tasks are increasingly typically developed for manufacturing methods, for example, as a microservice in a bigger software program. Data Science is a competitive field, and people are shortly building increasingly abilities and expertise.

You will achieve new expertise to design and maintain huge data ecosystems. To managers and recruiters that you've got the mandatory abilities they need in a data scientist. Hence, it offers an associate-degree and a specialist level which is extra advanced. So, coming to the most trending discussion for aspiring data scientists, that's, the data science certifications which are able to assist them to get hired. Below is the record of finest data science certifications with their cost and expiration. As we all know, the data scientist profession is among the hottest jobs in IT. What’s extra, it’s the most effective job you can get, according to data from Glassdoor.

As an data scientist, you have to know how to create a storyline around the data to make it easy for anyone to know. For instance, presenting a desk of data just isn't as efficient as sharing the insights from those data in a storytelling format. Using storytelling will allow you to properly talk your findings to your employers. Companies searching for a powerful data scientist are on the lookout for someone who can clearly and fluently translate their technical findings to a non-technical group, such as the Marketing or Sales departments. Check out our recent flash survey for more info on communication abilities for quantitative professionals. No doubt you’ve seen this phrase in all places recently, especially as it pertains to data scientists.

The cause for that is that data collection, data cleaning and processing is turning into very common these days as corporations need data to gather market and buyer data. Industries are buzzing about Big Data, and organizations are looking for hires with these in-demand, short-in-supply abilities. Improving your data analytics data right now means extra alternative—and more cash—for you sooner or later.

And which means demand for data scientists and associated positions may also go up. According to Peter Bailis, CEO of Sisu and co-principal investigator of the Stanford DAWN project, the job prospects for would-be data scientists are strong. No matter how you narrow it, data science is still a profitable area with plenty of opportunity, which is why universities proceed to add data science packages to their curriculums. According to data science training, there are more than 830 separate data science packages being provided from about 500 universities all over the world.

Though much of the mathematical heavy lifting is done by computer systems, understanding what makes this potential is crucial. Data scientists are tasked with figuring out what questions to pose, and how to make computers answer them. Therefore, the need for data scientists to have an excellent foundation in math is obvious. Understanding ideas like irrational and rational numbers assist data scientists write environment friendly and correct code. Software runs all the necessary statistical checks these days, however an data scientist nonetheless must possess the statistical sensibility to know which to take a look at to run when and the way to interpret the outcomes. Six Sigma are nice instruments to help data scientists and teams clear up actual world data science problems. The unique objectives, necessities and limitations of each industry outline every step that a data scientist takes.

Want to become a Data Scientist however never thought enterprise data is important? To turn out to be a good Data Scientist, you have to know your industry inside and out. You need to have a solid understanding of what business problems your company is making an attempt to unravel to be able to work in the direction of solving them by leveraging data in new and other ways. You need to be proficient in SQL as a Data Scientist that you can access the data easily in addition to work on it SQL can provide you deep insights into a database relying on your query. It also has concise instructions that can assist you to save lots of time and lessen the quantity of programming you should perform for tough queries.

Having a data science diploma in your resume may assist you to get a job. However, getting one usually takes years and costs tens if not tons of of thousands of dollars. I used it to retailer worth data, and thus realized 10x as much as I would have by just studying syntax. More importantly, should you’re not actively applying what you study, your research received it puts you together to do precise data science work. I can’t fully explain how immensely demotivating it's to be given a huge list of sources with none context. It’s akin to a teacher handing you a stack of textbooks and saying “learn all of those.” I struggled with this strategy when I was in school. If I had started studying data science this fashion, I by no means would have saved going.

None of those tasks could ever, by any stretch of the imagination, be thought-about simple. But the work that data scientists do is important for a business sector that more and more depends on huge data to drive efficiency.

A Masters of data science training is the preferred diploma supplied, it says, whereas about 135 schools supply data science packages on-line. We can’t stress enough how important are Python and R for the data science area in 2020. However, their strengths are their flaws, in terms of huge corporations. Python and R are each open supply frameworks that can be buggy or not well documented, in contrast to properly-established languages corresponding to MATLAB or C. One potential rationalization is that corporations don’t always understand the data scientist position properly.

Regardless of which ideas you choose to pursue, nonetheless, a basic understanding of statistics and statistical thinking is an absolute must-have for skilled data scientists. Python is the programming language to beat within the data science world.

In order to be efficient as a data scientist, people want to be able to perceive the info. Data scientists act as a bridge between complex, uninterpretable raw data and precise folks. Though cleansing, processing and analyzing data are important steps within the data science pipeline, this work is useless without efficient communication. Dave Holtz points out on the 360DigiTMG weblog, that the “data scientist” job title encompasses a wide range of positions, which may demand vastly completely different abilities from candidates.

So study SQL as it'll allow you to in understanding relational databases and add another feather to your cap as a Data Scientist. You shall be doing software improvement, data management, utility testing, and so on. as a Data Scientist. In common, Python and R are essentially the most commonly used languages for this objective. A Data Scientist creates predictive models and performs custom evaluation on the data in accordance with company necessities. This data science course hyderabad  has varied steps together with data extraction, exploration, visualization, and so forth. that require data of varied instruments and abilities. So let’s see the exhausting abilities that a Data Scientist should have to achieve success. Well, in today’s occasions that is someone who's multi-talented, works onerous, and is ready to go the additional mile.

In the long run, although, I suppose studying R is also very helpful since many statistics/ML textbooks use R for examples and workout routines. In truth, both books I talked about firstly use R, and until someone interprets everything to Python and posts it to Github, you gain the full advantage of the book. Created by Andrew Ng, maker of the well-known Stanford Machine Learning course, this is one of the highest rated data science programs on the internet. This course series is for these excited about understanding and dealing with neural networks in Python. Python is used on this data science course hyderabad , and there’s many lectures going by way of the intricacies of the various data science libraries to work through real-world, fascinating problems. This is one of the solely data science programs around that truly touches on each a part of the data science course of. The inclusion of probability and statistics courses makes this series from MIT a very properly-rounded curriculum for with the ability to understand data intuitively.

Holtz’s publication identifies 4 types of data scientist jobs and breaks down which skills are most significant for each. The expertise required of a data scientist may be sliced and diced in different ways.  360DigiTMG – 360DigiTMG hosts data science competitions the place you possibly can follow, hone your expertise with messy, actual world data, and sort out actual business problems. Employers take Kaggle rankings significantly, as they can be seen as related, hands-on project work.

For more information

360DigiTMG - Data Analytics, Data Science Course Training Hyderabad  

Address - 2-56/2/19, 3rd floor,, Vijaya towers, near Meridian school,, Ayyappa Society Rd, Madhapur,, Hyderabad, Telangana 500081

099899 94319

https://g.page/Best-Data-Science

[classbazaar]

Free Online Courses for Personal and Professional Development

In today's fast-paced digital world, learning has never been more accessible. With the rise of free online courses, anyone with an internet connection can now acquire new skills, deepen their knowledge, and even change their career path—all without spending a dime. Whether you're looking to improve your professional expertise, explore a new hobby, or simply quench your thirst for knowledge, free online courses are a powerful tool for self-improvement.

Why Choose Free Online Courses?

Free online courses offer an unparalleled opportunity for individuals to learn without the financial burden of traditional education. They are ideal for:

Career Advancement: Many free courses are designed by industry experts and prestigious institutions, offering skills that are directly applicable to your career.

Personal Development: From language learning to creative arts, you can explore a wide range of subjects that interest you.

Flexibility: Learn at your own pace, on your own schedule, and from the comfort of your home.

Accessibility: With just a device and internet connection, quality education is available to everyone, regardless of geographic location or financial status.

Popular Platforms Offering Free Online Courses

Several online platforms provide a vast selection of free courses across various disciplines. Some of the most popular platforms include:

Coursera: Partnering with top universities and organizations, Coursera offers free courses in fields such as business, technology, and humanities.

edX: Founded by Harvard and MIT, edX provides access to high-quality courses from leading institutions worldwide.

Udemy: Udemy's extensive library includes thousands of free courses on topics ranging from programming to personal development.

Khan Academy: Best known for its focus on K-12 education, Khan Academy also offers free courses in subjects like math, science, and economics.

How to Get the Most Out of Free Online Courses

To maximize the benefits of free online courses, it's essential to approach them with the right mindset and strategies. Here are some tips to help you succeed:

Set Clear Goals: Before starting a course, determine what you want to achieve. Whether it's mastering a new skill or gaining a certificate, having a clear goal will keep you motivated.

Create a Study Schedule: Allocate specific times during your week to study. Consistency is key to making progress.

Engage Actively: Take notes, participate in discussion forums, and complete assignments to reinforce your learning.

Practice Regularly: Apply what you've learned in real-life scenarios or through practice exercises to solidify your understanding.

Stay Committed: Free courses often require self-discipline. Stay committed to your learning journey, even when it gets challenging.

Top Categories of Free Online Courses

Free online courses are available in virtually every subject imaginable. Some of the top categories include:

1. Technology and Programming

In the ever-evolving tech world, staying updated with the latest skills is crucial. Free courses in this category cover everything from coding languages like Python and Java to data science, cybersecurity, and artificial intelligence.

2. Business and Management

For aspiring entrepreneurs or those looking to climb the corporate ladder, free courses in business strategy, leadership, marketing, and project management are invaluable.

3. Personal Development and Wellness

This category includes courses on mindfulness, mental health, time management, and more, helping you lead a balanced and fulfilling life.

4. Creative Arts

Explore your artistic side with free courses in photography, writing, graphic design, music, and other creative fields.

5. Languages

Learning a new language opens doors to new cultures and opportunities. Free language courses are available for everything from Spanish and French to less commonly taught languages like Korean or Swahili.

Benefits of Free Online Courses

Free online courses come with numerous benefits that make them an attractive option for learners of all ages:

Cost-Efficiency: As the name suggests, these courses are free, making education accessible to everyone, regardless of their financial situation.

Diverse Learning Opportunities: With courses available in a wide range of subjects, learners can explore new interests or deepen their expertise in specific areas.

Certificates of Completion: Many platforms offer certificates for free courses, which can be a valuable addition to your resume or LinkedIn profile.

Global Community: Online courses connect you with learners from around the world, providing a rich, multicultural learning experience.

Challenges of Free Online Courses

While free online courses offer many advantages, there are also some challenges to consider:

Lack of Structure: Without a set schedule or deadlines, it can be easy to procrastinate or lose focus.

Limited Interaction: Free courses may not offer the same level of interaction with instructors or peers as paid courses or traditional classrooms.

Certificate Fees: While the course content is free, some platforms may charge a fee for official certificates.

How to Choose the Right Free Online Course

Selecting the right course can be overwhelming, given the vast number of options available. Here’s how to make an informed decision:

Research the Course: Look for reviews, ratings, and testimonials from other learners.

Check the Syllabus: Ensure the course content aligns with your learning goals.

Assess the Instructor’s Credentials: Opt for courses taught by experienced professionals or institutions.

Consider the Course Length: Choose a course that fits your schedule, whether you prefer a short, intensive course or a more extended program.

Start Your Learning Journey Today

The world of free online courses is vast and full of potential. Whether you're a student, a professional, or a lifelong learner, there's something for everyone. At Class Bazaar, we curate the best free online courses across various platforms and disciplines, making it easier for you to find the right course to match your goals.

Ready to unlock new opportunities? Explore our free online courses and start learning today!

[analyticsindiam]

How Developers Can Benefit From Intel's Optimization Of TensorFlow

Abstraction is a common trait amongst the now widely used machine learning libraries or frameworks. Dusting off the nitty-gritty details under the rug and concentrating on implementing algorithms with more ease is what any data scientist would like to get their hands on. TensorFlow rose into prominence for the very same reason — abstraction.  Now with its latest library TensorFlow Graphics, it aims to address key computer vision challenges by incorporating the knowledge from graphics in the images, which in turn result in robust neural network architectures. TensorFlow is a widely-used Machine Learning framework in the deep learning arena, demanding efficient utilization of computational resources.  While efforts are being made to make Deep Learning more accessible through platforms like TensorFlow, companies like Intel® are tweaking TensorFlow to extract high performance.  The TensorFlow framework has been optimized1 using Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN) primitives, a popular performance library for deep learning applications.  TensorFlow follows a data flow paradigm for computations and it is a good model for doing parallelism.   TensorFlow is designed to be flexible, scalable and deployable. For example, new developers can get a quick start as this framework hides all complex distributed training and developers do not need to understand low level APIs. How Key Is Hardware For Deep Learning Inference Deep Learning inference can be done with two different strategies, each with different performance measurements and recommendations. The first is Max Throughput (MxT) and aims to process as many images per second, passing in batches of size > 1. For Max Throughput, best performance is achieved by exercising all the physical cores on a socket.  Real-time Inference (RTI) is an altogether different regime where we typically want to process a single image as fast as possible. Here the aim is to avoid penalties from excessive thread launching and orchestration between concurrent processes. The strategy is to confine and execute quickly. The following best known methods (BKMs) differ where noted with MxT RTI. How Intel® Affects Performance Most of the success of modern AI, especially deep learning algorithms, is due to its impressive results in image classification where near human-level has been observed. To explain the advantages that Intel® brings to the table, let's take the example2 of document classification. This capability can be used for document authentication which is a common task when opening a banking account, performing checks-in at the airport or showing a driver's license to a police officer. Today most document authentication tasks are done by humans, but AI is showing to be effective and is being increasingly employed for this activity. Any typical document classification task would contain the following steps: Binary Classifier: Label a given image as a Document or Not DocumentMulticlass Classifier: Label an image classified as a Document into either Front, Back, or UnfoldedOCR: This module receives an image and turn it into textImage Authentication: This module looks for a match between the picture available in the document with the real person picture available at a databaseText Authentication: This module looks for a match between the text available in the document with the real person data available at a database The Binary and Multiclass Classifier used in the experiments of this paper were implemented using Keras* high-level API available on TensorFlow. So, on the CPU, when Intel® Distribution for Python* along with Intel® Optimization for TensorFlow was used, around 70% to 80% improvement was observed only by installing Intel® Optimization for TensorFlow. This is done by setting Number of Threads to Execute in Parallel for Inter and Intra Operations in TensorFlow and Keras. To do this, set intra_op_parallelism_threads and OMP_NUM_THREADS equal to number of physical cores; and Set inter_op_parallelism_threads equal to number of sockets whereas, KMP_BLOCKTIME to zero; Intel® Xeon® Platinum CPU 8153 has 32 physical cores and 2 sockets, therefore intra_op_parallelism_threads is set to 32 and inter_op_parallelism_threads to 2 as shown in the code snippet below: import tensorflow as tf from tensorflow.keras import backend as K K.set_session( tf.Session(config=tf.ConfigProto(intra_op_parallelism_threads=32, inter_op_parallelism_threads=2))) Runtime options heavily effect TensorFlow performance. Understanding them will help get the best performance out of the Intel® Optimization of TensorFlow. intra_/inter_op_parallelism_threadsData layout Recommended settings (RTI)→ intra_op_parallelism = #physical cores Recommended settings → inter_op_parallelism = 2 tf_cnn_benchmarks usage (shell) python tf_cnn_benchmarks.py --num_intra_threads=cores --num_inter_threads=2 intra_op_parallelism_threads and inter_op_parallelism_threads are runtime variables defined in TensorFlow. ConfigProto. The ConfigProto is used for configuration when creating a session.  These two variables control number of cores to use. This runtime setting controls parallelism inside an operation. For instance, if matrix multiplication or reduction is intended to be executed in several threads, this variable should be set. TensorFlow will schedule tasks in a thread pool which contains intra_op_parallelism_threads threads.  These optimizations can result in orders of magnitude higher performance. For example, measurements are showing up to 70x higher performance for training and up to 85x higher performance for inference on Intel® Xeon Phi™ processor 7250.  The comparison was taken using a default environment with libraries from official pip channel (baseline) and an Intel® optimized environment where Intel® Distribution for Python* and Intel® Optimization for TensorFlow* were installed. 

Source: Intel The results show that there has been a 3.1X speedup when training a binary image classifier and 3.6x speedup when training a multiclass image classifier.  For even better performance, batch size was increased in the optimized environment. Increasing batch size delivered a boosted performance but led to an accuracy drop on both classifiers.  Validation accuracy drop on binary classifier went from 98% to 85% and on the multiclass classifier from 95% to 44%. We can also take advantage of large memory size available on Intel® Xeon® Scalable processors and increase the batch size to process more images at the same time while computing the gradients of a Neural Network. Increasing the batch size can reduce the execution time for training on CPUs, but it may also have an impact on testing accuracy, therefore this step should be taken carefully to decide if the gain in execution time is worth the loss in accuracy. Conclusion TensorFlow’s machine learning platform has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications. Now, with the release of TensorFlow 2.0, more focus is aimed at developer productivity, simplicity, and ease of use. There are multiple changes in TensorFlow 2.0 to make TensorFlow users more productive. TensorFlow 2.0 removes redundant APIs, makes APIs more consistent (Unified RNNs, Unified Optimizers), and improved integration with the Python runtime with Eager execution. Optimizing TensorFlow means deep learning applications built using this widely available and widely applied framework can now run much faster on Intel® processors to increase flexibility, accessibility, and scale.  The Intel® Xeon Phi processor, for example, is designed to scale out in a near-linear fashion across cores and nodes to dramatically reduce the time to train machine learning models.  The collaboration between Intel® and Google to optimize TensorFlow is part of ongoing efforts to make AI more accessible to developers and data scientists, and to enable AI applications to run wherever they’re needed on any kind of device—from the edge to the cloud. Intel® believes this is the key to creating the next-generation of AI algorithms and models to solve the most pressing problems in business, science, engineering, medicine, and society. Sources: 1TensorFlow Optimizations on Modern Intel® Architecture 2Accelerating Document Classification (Training) using Intel® Optimization for TensorFlow Read the full article

[all-data-by-jacob-public]

ML, DL 공부 조언들

https://hackernoon.com/what-leading-artificial-intelligence-course-should-you-take-and-what-should-you-do-after-261a933bb3da

https://www.quora.com/What-should-I-do-after-completion-of-all-the-courses-in-Andrew-Ng-Deep-Learning-Specialisation-I-would-like-to-specialize-in-convolutional-neural-networks

If I were you, I would do this:

Go and watch Neural networks class - Université de Sherbrooke - YouTube.

Start reading Deep Learning Book and slowly work through the theory and practice/implement in python or (maybe Julia)

[2.5, in parallel while reading the book] Read this list of highly cited papers terryum/awesome-deep-learning-papers and try implementing those [and also follow this thread on twitter. ]

Keep up to date with Reddit’s Machine Learning • r/MachineLearning.

Start learning Linear Dynamical Systems. EE263: Introduction to Linear Dynamical Systems.

More maths!

Look at areas where deep learning can be applicable such as computer vision, speech, audio, graphics etc. Why not fuse AR+Deep learning?

Apply to research labs and programs.

Have fun.

Maybe look at differentiable programming and computational neuroscience.

It depends on where you want to go!

You mentioned that you are interested in specializing in CNNs. That’s great that you found a topic you are interested in! Are you more interested in understanding the ideas behind ML and develop new techniques how to improve them? Or do you just want to understand existing techniques and how to use them? I would advise you to choose your literature accordingly!

First case: Read about the background ideas that lead to the ML achievements we have today. For example

Information Theory, Inference and Learning Algorithms by David J. C. MacKay

The Elements of Statistical Learning by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie

Pattern Recognition and Machine Learning by Christopher Bishop

Convex Optimization by Lieven Vandenberghe and Stephen P. Boyd

Second case: Research the newest techniques you are interested in, check out youtube videos / github repositories of the implementations and play around with them!

I want to stress that you learn more and better if you do want you like - so don’t force yourself to read a whole book! Read some chapters you are interested in, play around with some implementations, and go back to the theory. Follow your focus and try do understand the bigger picture instead of a specific architecture or other details. Good luck!

nice! if you are really interested in cnn then you should choose to learn research papers on this topic and try to implement those things, it will enrich you and there are some links you can follow.

Convolutional Neural Networks for Visual Recognition.[1]

or you can choose fast.ai · Making neural nets uncool again course by Jeromy Howard. try to improve yourself with these courses happy learning.

Footnotes

[1] CS231n Convolutional Neural Networks for Visual Recognition

https://www.quora.com/After-the-Andrew-Ng-course-on-machine-learning-can-I-start-learning-deep-learning-or-is-more-study-required

Assuming that you understand basic building blocks of ML, you could first get hands-on understanding with python (primarily utility libraries).

You can learn to use numpy, pandas, matplotlib. and try playing a bit with data manipulation.

Try a few notebooks / tutorials from github for any one of ML algorithm (I usually recommend SGD based recommendation alog but SVM will be good too, though a little difficult).

Once you have understanding of python good enough to be able to read code then you could head on to any of these courses:

Deep Learning | Udacity

fast.ai · Making neural nets uncool again

Both are excellent for starters.

If you like more of use-case based learning of AI then do consider signing up here -> AmpLabs - Up your game This is something i have been working on for a time saving, hands-on learning of AI.

All the best!

Andrew Ng's Coursera course is adapted from the Stanford class (CS229). Abu-Mustafa (Caltech) refers to it as a watered-down version. Even so, Ng does a great job making the topic approachable and practical.

You have two options and they're not mutually exclusive:

1. Go deeper into the algorithms: There are other ML courses out there. Many of them are quite "Mathy", and with the right preparation in Calculus/Linear Algebra/Probability, you will enjoy them. To deepen your understanding, you could go through original CS229 material, or take Caltech’s “Learning from Data” course by Abu-Mustafa. Furthermore, I suggest checking out Hinton's "Neural Networks" course, or "CS231n: Convolutional Neural Networks for Visual Recognition." These would introduce you to Deep Learning (some of which you've already covered with Ng). Caveat: DL is a rapidly moving field, and some think that the ANN class on Coursera is already dated.

2. Apply what you've learnt: Ultimately, this is what it's all about! Check out kaggle for real-world problems. Heck, you may even win a prize :-)

[maritzaerwin]

8 Fantastic Platforms for Free Online Educational Content

In a world where many of our most important interactions seem to be taking place online, we are always on the lookout for all resources, including educational content, at hand to succeed in the digital world. 

Something particularly true when it comes to ways of advancing our learning and self-development.

Despite the challenges we experience in 2020, today, we live in the best era to take advantage of e-learning content. Entrepreneurs and startups are doubling down on this unique opportunity to effectively promote their material, such as educational videos and courses, to wider audiences.

Such is the great content waiting for you online that we want to take on the task of introducing you to some of the best platforms for free educational content that you can start learning from today. 

And maybe more importantly, why you should!

The Impact of Educational Content Platforms

Whether you want to improve your knowledge of science and history or to acquire new technical skills like programming to improve your resume, there’s content for you on the web that will help you expand your capacities.

But what exactly makes virtual programs so effective? Why are many even preferring the online format over the traditional classroom setting?

Consider the following e-learning trends:

E-learning programs are very personalized, which motivates learners to develop the soft skills and knowledge they need and care about.

Online educational content platforms tend to favor video-based learning, which significantly helps the student retain knowledge and engage more with the content.

The best learning modules will often feature top experts in different areas as instructors or speakers—something you don’t always get even at university!

Today we even see a move towards the gamification of the standard educational practices.

These are just a few reasons that play in favor of online education. But which platforms best implement these principles?

Best Platforms for Free Online Educational Content

1. Scholastic’s ‘Learn at Home’ Platform for Young Students

In a time where many kids are living their educational content experience from home, Scholastics is a great solution that supplies content for all grade levels—from Pre-K and Kindergarten to grades 1 to 5 and higher grades.

Scholastic offers free resources to parents and teachers to keep young children engaged during their learning journey. The platform is accessible from all devices, including smartphones, and its dashboard comes with handy resources and instructions to effectively guide the lessons.

The program is packed with material to work with at least 3 hours five days of the week. It includes theory, as well as activities and projects that the younger can practice with dedication.

The content is balanced between readings, videos, and even games that, for sure, won’t bore the young learner. But the lessons are developed to emphasize integration: instead of presenting the topics in a disconnected fashion, they are organized to show the connection between subjects.

With this platform at hand, learning from home can become a fun, enriching experience!

2. Codecademy’s Free Coding Courses

Codecademy’s mission is “to rethink education from the bottom up.” This is a platform that takes seriously the job of helping individuals learn and succeed in an online world that’s always changing, and that’s long left the model of textbook education behind.

The service focuses on providing knowledge on the tech and computer skills. Some of these include:

Data science.

Web development.

Programming.

Computer science.

Its instructors teach different programming languages, such as Python, SQL, and Javascript. But they never stop innovating. The site is constantly expanding its curriculum to meet new challenges.

If what’s been said so far has not sparked your interest in exploring the platform, wait until you hear the rest: Codecademy follows you through your learning progress in a personalized way.

Once you choose what you want to learn, you get to practice it in real-time. In the process, you will be receiving individual guidance in the form of feedback. You also have the chance to take on projects to put your skills to the test, start building your own portfolio, and finally land into your dream job.

Additionally, the service has special offers for businesses and schools, whose plans start at reasonable prices. In a time where most of our key professional and social interactions are taking place online, this is an invaluable asset to upskill your team or students.

3. Open Culture’s Massive Library of Educational Content

Open Culture is a very useful repository that collects, curates, and gives you access to material and courses found all over the internet. This is the platform you want to come to when you are looking for content that you don’t know where to find.

It hosts all kinds of content: not only will you find course lectures and transcripts as well as blog posts there—the platform also leads you to places where you can find free movies, audiobooks, and even professional podcasts.

The contents are neatly organized in browsed categories that are frequently updated. You can bet you’ll find almost any topic that comes to mind there: from standard school-level courses on math and literature to the history of jazz and fashion, and the latest news in Broadway.

You can join for free starting today by subscribing to their newsletter. There you’ll receive daily recommendations of thought-provoking readings, films, cultural reviews, and almost anything you can imagine!

4. Khan Academy’s Compendium of Academic Courses

The extraordinary rise of Khan Academy from a relatively unknown startup to a world-renowned platform should tell us something about the big opportunities in developing educational content platforms.

Khan Academy hosts hundreds of courses and a library that can be used as a great support for classrooms. In fact, about 70 million people used the platform and participated in their classes.

The courses cover a wide variety of topics that are essential for the young student’s (and the not so young’s) learning experience, including math, computing, science, history, and art. They have been translated in more than 36 languages, and there are Spanish, French, and Portuguese versions of the site.

But what’s truly valuable is the platform’s emphasis on its ideal that #YouCanLearnAnything. Through resources such as instructional educational videos, students are encouraged to learn at their own pace in building blocks according to their personal needs and interests.

Khan Academy is also very convenient for parents and teachers, as they can use the platform’s personalized dashboards to track the student’s learning process and, in that way, identify the areas where they need more help.

5. Future Learn’s Assortment of College Level Courses on Various Topics

If you are interested in approaching excellent college-level courses, then you should explore the options that Future Learn holds for you.

There you will find courses taught by top experts in academia and industry, whose contents you can audit for free. But if you are fully committed to taking your educational development one step further, the platform has plans that let you participate in full programs to earn a certified degree and formal accreditation.

But the opportunities don’t end there! One of the most exciting aspects of Future Learn is that it’s a community of fellow students that mutually supports its members. You’ll join a network of millions of students around the world with whom you can share your experiences and progress.

The subjects mainly focus on the classic curricula you find in an academic environment: you have classes on history, science, business, IT, and computer science. They are perfectly balanced between lectures, quizzes, videos, and tests to probe your knowledge.

But its modules on practical skills such as teaching and study methods are also very relevant, and some of the most popular on the web.

6. TED-Ed’s Motivational Talks

TED events are well-publicized, and for good reason: you get to see some of the best speakers in the world engaging with interesting, important, and relevant topics through talks and presentations.

TED’s website and YouTube channels are very useful places you can turn to when you have a question in your mind that you want to address. The talks are very entertaining as a rule, and the format is bit-sized, which means that you can always take 10 or 20 minutes off your schedule to learn something new.

The presentations often include slides and pictures, and sometimes they will be adapted to animation. Each talk is unique, as no two speakers approach the same subject from the same viewpoint. Each will give it his or her own personal imprint, and it’s not unusual to see some speakers be more technical, while others lean more heavily on things like humor to get their ideas across.

Another aspect that’s part of the TED formula is the speaker’s emphasis on the practical, life-changing implications of the topics they discuss. This commitment to the importance of ideas is reflected in the website, which often couples the videos with supplemental material and questions.

7. MoMA’s Series of Art-Related Classes

If there’s an area many of us haven’t been trained in, that has to be art critique and analysis. Judging art is a complex skill that demands deep work and background knowledge that’s not easily available.

It is a shame, really, since being able to judge and understand art is an immensely valuable skill that can enhance our appreciation of works and serve as a springboard to meaningful conversations with our friends. 

Fortunately, we can fill this gap with the help of the free online courses created by the Museum of Modern Art in New York. Its contents are hosted by Coursera, and they feature topics that cover many levels of complexity, none requiring previous expertise.

Some of the most interesting include:

What Is Contemporary Art?

In the Studio: Postwar Abstract Painting.

Fashion as Design.

Art & Inquiry: Museum Teaching Strategies for Your Classroom.

In those classes, you’ll join MoMA’s top experts and curators to explore the hidden wonders in some of the best works of art in history.

But what will blow your mind is the high-quality of the content: there you’ll see beautiful, curated images and shots of the works and exhibitions the museum hosts, like you won’t find anywhere else.

So now you know: there’s a solution for our general lack of knowledge in art waiting for us. After taking a couple of classes, you’ll never feel left behind again next time someone asks your opinion about a great painting or sculpture.

8. Stanford Online’s Higher Education Programs

Stanford Online gathers some of the best minds you find at the University of Stanford’s campus. It is part of the Stanford Center for Professional Development, which since 1995 has been one of the world pioneers in the move towards distance learning.

The developers create their material through the collaboration of third-party organizations and platforms, such as Coursera, Edx, and iTunes. The offers include dozens of free college-level courses, as well as graduate and professional custom program that are open for credentials.

Stanford is also known for hosting other key resources for professionals and academics, like the renowned Stanford Encyclopedia of Philosophy, which is accessible to anyone who wants to engage with profound thinkers and expand his knowledge.

Although the list of courses is not as extensive as that of other hubs, all of Stanford’s modules are of top-notch quality. Another thing that makes this platform worthy of attention is that the contents are up to date with the most important issues and challenges that we face as a society.

Start Expanding Your Horizons

Today, the barriers of money and distance are not an obstacle to getting the best possible education. With virtually any electronic device and reliable Wi-Fi connection, you can have access to resources that have nothing to envy to the world’s best universities.

We’ve taken you through truly fantastic platforms that you can use either for improving your knowledge and skills as a professional, as well as for helping your children or students.

As you’ve seen, the opportunities are immense, and there’s no fear of not being able to adapt: most platforms strive to promote ways of putting your skills into practice.

There are many other platforms like these that are waiting for you to discover them. What will you start learning today?

8 Fantastic Platforms for Free Online Educational Content published first on https://skillsireweb.tumblr.com/

[isearchgoood]

Intro to Python - Whiteboard Friday

Posted by BritneyMuller

Python is a programming language that can help you uncover incredible SEO insights and save you time by automating time-consuming tasks. But for those who haven't explored this side of search, it can be intimidating. In this episode of Whiteboard Friday, Britney Muller and a true python expert named Pumpkin offer an intro into a helpful tool that's worth your time to learn.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Hey, Moz fans. Welcome to another edition of Whiteboard Friday. Today we're talking all about introduction to Python, which is why I have a special co-host here. She is a ball python herself, total expert. Her name is Pumpkin, and she's the best. 

What is Python?

So what is Python? This has been in the industry a lot lately. There's a lot of commotion that you should know how to use it or know how to talk about it. Python is an open source, object-oriented programming language that was created in 1991.

Simpler to use than R

Some fun facts about Python is it's often compared to R, but it's arguably more simple to use. The syntax just oftentimes feels more simple and common-sense, like when you're new to programming. 

Big companies use it

Huge companies use it. NASA, Google, tons of companies out there use it because it's widely supported.

It's open source

It is open source. So pretty cool. While we're going through this Whiteboard Friday, I would love it if we would do a little Python programming today. So I'm just going to ask that you also visit this in another tab, python.org/downloads. Download the version for your computer and we'll get back to that. 

Why does Python matter?

So why should you care? 

Automates time-consuming tasks

Python is incredibly powerful because it helps you automate time-consuming tasks. It can do these things at scale so that you can free up your time to work on higher-level thinking, to work on more strategy. It's really, really exciting where these things are going. 

Log file analysis

Some examples of that are things like log file analysis. Imagine if you could just set up an automated system with Python to alert you any time one of your primary pages wasn't being crawled as frequently as it typically is. You can do all sorts of things. Let's say Google crawls your robots.txt and it throws out a server error, which many of you know causes huge problems. It can alert you. You can set up scripts like that to do really comprehensive tasks. 

Internal link analysis

Some other examples, internal link analysis, it can do a really great job of that. 

Discover keyword opportunities

It can help you discover keyword opportunities by looking at bulk keyword data and identifying some really important indicators. 

Image optimization

It's really great for things like image optimization. It can auto tag and alt text images. It can do really powerful things there. 

Scrape websites

It can also scrape the websites that you're working with to do really high volume tasks. 

Google Search Console data analysis

It can also pull Google Search Console data and do analysis on those types of things.

I do have a list of all of the individuals within SEO who are currently doing really, really powerful things with Python. I highly suggest you check out some of Hamlet Batista's recent scripts where he's using Python to do all sorts of really cool SEO tasks. 

How do you run Python?

What does this even look like? So you've hopefully downloaded Python as a programming language on your computer. But now you need to run it somewhere. Where does that live? 

Set up a virtual environment using Terminal

So first you should be setting up a virtual environment. But for the purpose of these examples, I'm just going to ask that you pull up your terminal application.

It looks like this. You could also be running Python within something like Jupyter Notebook or Google Colab. But just pull up your terminal and let's check and make sure that you've downloaded Python properly. 

Check to make sure you've downloaded Python properly

So the first thing that you do is you open up the terminal and just type in "python --version." You should see a readout of the version that you downloaded for your computer. That's awesome. 

Activate Python and perform basic tasks

So now we're just going to activate Python and do some really basic tasks. So just type in "python" and hit Enter. You should hopefully see these three arrow things within your terminal. From here, you can do something like print ("Hello, World!"). So you enter it exactly like you see it here, hit Enter, and it will say "Hello, World!" which is pretty cool.



You can also do fun things like just basic math. You can add two numbers together using something like this. So these are individual lines. After you complete the print (sum), you'll see the readout of the sum of those two numbers. You can randomly generate numbers. I realize these aren't direct SEO applications, but these are the silly things that give you confidence to run programs like what Hamlet talks about.

Have fun — try creating a random number generator

So I highly suggest you just have fun, create a little random number generator, which is really cool. Mine is pulling random numbers from 0 to 100. You can do 0 to 10 or whatever you'd like. A fun fact, after you hit Enter and you see that random number, if you want to continue, using your up arrow will pull up the last command within your terminal.

It even goes back to these other ones. So that's a really quick way to rerun something like a random number generator. You can just crank out a bunch of them if you want for some reason. 

Automating different tasks

This is where you can start to get into really cool scripts as well for pulling URLs using Requests HTML. Then you can pull unique information from web pages.

You can pull at bulk tens of thousands of title tags within a URL list. You can pull things like H1s, canonicals, all sorts of things, and this makes it incredibly easy to do it at scale. One of my favorite ways to pull things from URLs is using xpath within Python.

This is a lot easier than it looks. So this might be an xpath for some websites, but websites are marked up differently. So when you're trying to pull something from a particular site, you can right-click into Chrome Developer Tools. Within Chrome Developer Tools, you can right-click what it is that you're trying to scrape with Python.

You just select "Copy xpath," and it will give you the exact xpath for that website, which is kind of a fun trick if you're getting into some of this stuff. 

Libraries

What are libraries? How do we make this stuff more and more powerful? Python is really strong on its own, but what makes it even stronger are these libraries or packages which are add-ons that do incredible things.

This is just a small percentage of libraries that can do things like data collection, cleaning, visualization, processing, and deployment. One of my favorite ways to get some of the more popular packages is just to download Anaconda, because it comes with all of these commonly used, most popular packages.

So it's kind of a nice way to get all of it in one spot or at least most of them. 

Learn more

So you've kind of dipped your toes and you kind of understand what Python is and what people are using it for. Where can you learn more? How can you start? Well, Codecademy has a really great Python course, as well as Google, Kaggle, and even the Python.org website have some really great resources that you can check out.

This is a list of individuals I really admire in the SEO space, who are doing incredible work with Python and have all inspired me in different ways. So definitely keep an eye on what they are up to:

Hamlet Batista

Ruth Everett

Tom Donahue

Kristin Tynski

Paul Shapiro

Tyler Reardon

JR Oakes

Hulya Coban

@Jessthebp

But yeah, Pumpkin and I have really enjoyed this, and we hope you did too. So thank you so much for joining us for this special edition of Whiteboard Friday. We will see you soon. Bye, guys.

Video transcription by Speechpad.com

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[luongthuyvy]

Intro to Python - Whiteboard Friday

Posted by BritneyMuller

Python is a programming language that can help you uncover incredible SEO insights and save you time by automating time-consuming tasks. But for those who haven't explored this side of search, it can be intimidating. In this episode of Whiteboard Friday, Britney Muller and a true python expert named Pumpkin offer an intro into a helpful tool that's worth your time to learn.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Hey, Moz fans. Welcome to another edition of Whiteboard Friday. Today we're talking all about introduction to Python, which is why I have a special co-host here. She is a ball python herself, total expert. Her name is Pumpkin, and she's the best. 

What is Python?

So what is Python? This has been in the industry a lot lately. There's a lot of commotion that you should know how to use it or know how to talk about it. Python is an open source, object-oriented programming language that was created in 1991.

Simpler to use than R

Some fun facts about Python is it's often compared to R, but it's arguably more simple to use. The syntax just oftentimes feels more simple and common-sense, like when you're new to programming. 

Big companies use it

Huge companies use it. NASA, Google, tons of companies out there use it because it's widely supported.

It's open source

It is open source. So pretty cool. While we're going through this Whiteboard Friday, I would love it if we would do a little Python programming today. So I'm just going to ask that you also visit this in another tab, python.org/downloads. Download the version for your computer and we'll get back to that. 

Why does Python matter?

So why should you care? 

Automates time-consuming tasks

Python is incredibly powerful because it helps you automate time-consuming tasks. It can do these things at scale so that you can free up your time to work on higher-level thinking, to work on more strategy. It's really, really exciting where these things are going. 

Log file analysis

Some examples of that are things like log file analysis. Imagine if you could just set up an automated system with Python to alert you any time one of your primary pages wasn't being crawled as frequently as it typically is. You can do all sorts of things. Let's say Google crawls your robots.txt and it throws out a server error, which many of you know causes huge problems. It can alert you. You can set up scripts like that to do really comprehensive tasks. 

Internal link analysis

Some other examples, internal link analysis, it can do a really great job of that. 

Discover keyword opportunities

It can help you discover keyword opportunities by looking at bulk keyword data and identifying some really important indicators. 

Image optimization

It's really great for things like image optimization. It can auto tag and alt text images. It can do really powerful things there. 

Scrape websites

It can also scrape the websites that you're working with to do really high volume tasks. 

Google Search Console data analysis

It can also pull Google Search Console data and do analysis on those types of things.

I do have a list of all of the individuals within SEO who are currently doing really, really powerful things with Python. I highly suggest you check out some of Hamlet Batista's recent scripts where he's using Python to do all sorts of really cool SEO tasks. 

How do you run Python?

What does this even look like? So you've hopefully downloaded Python as a programming language on your computer. But now you need to run it somewhere. Where does that live? 

Set up a virtual environment using Terminal

So first you should be setting up a virtual environment. But for the purpose of these examples, I'm just going to ask that you pull up your terminal application.

It looks like this. You could also be running Python within something like Jupyter Notebook or Google Colab. But just pull up your terminal and let's check and make sure that you've downloaded Python properly. 

Check to make sure you've downloaded Python properly

So the first thing that you do is you open up the terminal and just type in "python --version." You should see a readout of the version that you downloaded for your computer. That's awesome. 

Activate Python and perform basic tasks

So now we're just going to activate Python and do some really basic tasks. So just type in "python" and hit Enter. You should hopefully see these three arrow things within your terminal. From here, you can do something like print ("Hello, World!"). So you enter it exactly like you see it here, hit Enter, and it will say "Hello, World!" which is pretty cool.



You can also do fun things like just basic math. You can add two numbers together using something like this. So these are individual lines. After you complete the print (sum), you'll see the readout of the sum of those two numbers. You can randomly generate numbers. I realize these aren't direct SEO applications, but these are the silly things that give you confidence to run programs like what Hamlet talks about.

Have fun — try creating a random number generator

So I highly suggest you just have fun, create a little random number generator, which is really cool. Mine is pulling random numbers from 0 to 100. You can do 0 to 10 or whatever you'd like. A fun fact, after you hit Enter and you see that random number, if you want to continue, using your up arrow will pull up the last command within your terminal.

It even goes back to these other ones. So that's a really quick way to rerun something like a random number generator. You can just crank out a bunch of them if you want for some reason. 

Automating different tasks

This is where you can start to get into really cool scripts as well for pulling URLs using Requests HTML. Then you can pull unique information from web pages.

You can pull at bulk tens of thousands of title tags within a URL list. You can pull things like H1s, canonicals, all sorts of things, and this makes it incredibly easy to do it at scale. One of my favorite ways to pull things from URLs is using xpath within Python.

This is a lot easier than it looks. So this might be an xpath for some websites, but websites are marked up differently. So when you're trying to pull something from a particular site, you can right-click into Chrome Developer Tools. Within Chrome Developer Tools, you can right-click what it is that you're trying to scrape with Python.

You just select "Copy xpath," and it will give you the exact xpath for that website, which is kind of a fun trick if you're getting into some of this stuff. 

Libraries

What are libraries? How do we make this stuff more and more powerful? Python is really strong on its own, but what makes it even stronger are these libraries or packages which are add-ons that do incredible things.

This is just a small percentage of libraries that can do things like data collection, cleaning, visualization, processing, and deployment. One of my favorite ways to get some of the more popular packages is just to download Anaconda, because it comes with all of these commonly used, most popular packages.

So it's kind of a nice way to get all of it in one spot or at least most of them. 

Learn more

So you've kind of dipped your toes and you kind of understand what Python is and what people are using it for. Where can you learn more? How can you start? Well, Codecademy has a really great Python course, as well as Google, Kaggle, and even the Python.org website have some really great resources that you can check out.

This is a list of individuals I really admire in the SEO space, who are doing incredible work with Python and have all inspired me in different ways. So definitely keep an eye on what they are up to:

Hamlet Batista

Ruth Everett

Tom Donahue

Kristin Tynski

Paul Shapiro

Tyler Reardon

JR Oakes

Hulya Coban

@Jessthebp

But yeah, Pumpkin and I have really enjoyed this, and we hope you did too. So thank you so much for joining us for this special edition of Whiteboard Friday. We will see you soon. Bye, guys.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

Intro to Python - Whiteboard Friday Theo dõi các thông tin khác tại: https://foogleseo.blogspot.com Intro to Python - Whiteboard Friday posted first on https://foogleseo.blogspot.com/ #FoogleSEO #luongthuyvy Nguồn: http://bit.ly/2QFTvnK #luongthuyvy

[whitelabelseoreseller]

Intro to Python - Whiteboard Friday

Posted by BritneyMuller

Python is a programming language that can help you uncover incredible SEO insights and save you time by automating time-consuming tasks. But for those who haven't explored this side of search, it can be intimidating. In this episode of Whiteboard Friday, Britney Muller and a true python expert named Pumpkin offer an intro into a helpful tool that's worth your time to learn.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Hey, Moz fans. Welcome to another edition of Whiteboard Friday. Today we're talking all about introduction to Python, which is why I have a special co-host here. She is a ball python herself, total expert. Her name is Pumpkin, and she's the best. 

What is Python?

So what is Python? This has been in the industry a lot lately. There's a lot of commotion that you should know how to use it or know how to talk about it. Python is an open source, object-oriented programming language that was created in 1991.

Simpler to use than R

Some fun facts about Python is it's often compared to R, but it's arguably more simple to use. The syntax just oftentimes feels more simple and common-sense, like when you're new to programming. 

Big companies use it

Huge companies use it. NASA, Google, tons of companies out there use it because it's widely supported.

It's open source

It is open source. So pretty cool. While we're going through this Whiteboard Friday, I would love it if we would do a little Python programming today. So I'm just going to ask that you also visit this in another tab, python.org/downloads. Download the version for your computer and we'll get back to that. 

Why does Python matter?

So why should you care? 

Automates time-consuming tasks

Python is incredibly powerful because it helps you automate time-consuming tasks. It can do these things at scale so that you can free up your time to work on higher-level thinking, to work on more strategy. It's really, really exciting where these things are going. 

Log file analysis

Some examples of that are things like log file analysis. Imagine if you could just set up an automated system with Python to alert you any time one of your primary pages wasn't being crawled as frequently as it typically is. You can do all sorts of things. Let's say Google crawls your robots.txt and it throws out a server error, which many of you know causes huge problems. It can alert you. You can set up scripts like that to do really comprehensive tasks. 

Internal link analysis

Some other examples, internal link analysis, it can do a really great job of that. 

Discover keyword opportunities

It can help you discover keyword opportunities by looking at bulk keyword data and identifying some really important indicators. 

Image optimization

It's really great for things like image optimization. It can auto tag and alt text images. It can do really powerful things there. 

Scrape websites

It can also scrape the websites that you're working with to do really high volume tasks. 

Google Search Console data analysis

It can also pull Google Search Console data and do analysis on those types of things.

I do have a list of all of the individuals within SEO who are currently doing really, really powerful things with Python. I highly suggest you check out some of Hamlet Batista's recent scripts where he's using Python to do all sorts of really cool SEO tasks. 

How do you run Python?

What does this even look like? So you've hopefully downloaded Python as a programming language on your computer. But now you need to run it somewhere. Where does that live? 

Set up a virtual environment using Terminal

So first you should be setting up a virtual environment. But for the purpose of these examples, I'm just going to ask that you pull up your terminal application.

It looks like this. You could also be running Python within something like Jupyter Notebook or Google Colab. But just pull up your terminal and let's check and make sure that you've downloaded Python properly. 

Check to make sure you've downloaded Python properly

So the first thing that you do is you open up the terminal and just type in "python --version." You should see a readout of the version that you downloaded for your computer. That's awesome. 

Activate Python and perform basic tasks

So now we're just going to activate Python and do some really basic tasks. So just type in "python" and hit Enter. You should hopefully see these three arrow things within your terminal. From here, you can do something like print ("Hello, World!"). So you enter it exactly like you see it here, hit Enter, and it will say "Hello, World!" which is pretty cool.



You can also do fun things like just basic math. You can add two numbers together using something like this. So these are individual lines. After you complete the print (sum), you'll see the readout of the sum of those two numbers. You can randomly generate numbers. I realize these aren't direct SEO applications, but these are the silly things that give you confidence to run programs like what Hamlet talks about.

Have fun — try creating a random number generator

So I highly suggest you just have fun, create a little random number generator, which is really cool. Mine is pulling random numbers from 0 to 100. You can do 0 to 10 or whatever you'd like. A fun fact, after you hit Enter and you see that random number, if you want to continue, using your up arrow will pull up the last command within your terminal.

It even goes back to these other ones. So that's a really quick way to rerun something like a random number generator. You can just crank out a bunch of them if you want for some reason. 

Automating different tasks

This is where you can start to get into really cool scripts as well for pulling URLs using Requests HTML. Then you can pull unique information from web pages.

You can pull at bulk tens of thousands of title tags within a URL list. You can pull things like H1s, canonicals, all sorts of things, and this makes it incredibly easy to do it at scale. One of my favorite ways to pull things from URLs is using xpath within Python.

This is a lot easier than it looks. So this might be an xpath for some websites, but websites are marked up differently. So when you're trying to pull something from a particular site, you can right-click into Chrome Developer Tools. Within Chrome Developer Tools, you can right-click what it is that you're trying to scrape with Python.

You just select "Copy xpath," and it will give you the exact xpath for that website, which is kind of a fun trick if you're getting into some of this stuff. 

Libraries

What are libraries? How do we make this stuff more and more powerful? Python is really strong on its own, but what makes it even stronger are these libraries or packages which are add-ons that do incredible things.

This is just a small percentage of libraries that can do things like data collection, cleaning, visualization, processing, and deployment. One of my favorite ways to get some of the more popular packages is just to download Anaconda, because it comes with all of these commonly used, most popular packages.

So it's kind of a nice way to get all of it in one spot or at least most of them. 

Learn more

So you've kind of dipped your toes and you kind of understand what Python is and what people are using it for. Where can you learn more? How can you start? Well, Codecademy has a really great Python course, as well as Google, Kaggle, and even the Python.org website have some really great resources that you can check out.

This is a list of individuals I really admire in the SEO space, who are doing incredible work with Python and have all inspired me in different ways. So definitely keep an eye on what they are up to:

Hamlet Batista

Ruth Everett

Tom Donahue

Kristin Tynski

Paul Shapiro

Tyler Reardon

JR Oakes

Hulya Coban

@Jessthebp

But yeah, Pumpkin and I have really enjoyed this, and we hope you did too. So thank you so much for joining us for this special edition of Whiteboard Friday. We will see you soon. Bye, guys.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

from The Moz Blog http://tracking.feedpress.it/link/9375/13142491

[milescpareview]

5 Advice you need to hear before starting your career in AI-ML

Are you still in doubt about taking-up the AI-challenge in 2021?

If you have impulsively responded to the hype around AI and jumped on to be the next AI maestro, know that it’s worth every penny. Before starting with AI-ML it’s important to have domain awareness, and how you can contribute to the community after your certification. 

It’s important to set your goals if you want to practice your skills in real-world applications solving business problems. Introduction to Data Science will help you transition to concepts of Artificial Intelligence, Deep Learning, and Machine Learning. 

Here are 5 suggestions to help you ace your AI-ML learning journey

1) Say Yes to Mathematics-

There is a notion that AI programs are as smart as the developer wants them to be. Let’s not remember the sleepless nights before a Maths exam at school. While AI is biased towards learners with logical thinking skills and a number cruncher, new-found AI geeks and champions are those who have mastered basic Maths skills. The reason behind the rush for maths is because Machine Learning (ML) algorithms are heavily dependent on maths, probability, and statistics. You do not need to know advanced Math concepts like Calculus and Trigonometry but AI/ML courses require you to have knowledge of probability, critical concepts of linear algebra (notation, operations, and matrics factorization), and statistics. You could also look for free courses on ML mathematics designed specifically for beginners. 

2) Learning the ABCs of Coding -

Keeping the facts straight, machines cannot think! It’s us who train them to learn, hear, and sense and feed them with instructions and have a language of their own. Hence it’s important to be acquainted with programming languages, specifically Python and R before starting your AI learning journey. As you are not the professional who is vibing with AI, there are a bunch of free tutorials to keep you updated. A bonus tip - start following python and data science pages in social media like the Miles Education AI social media page. This way you will feel comfortable with the concepts of AI-ML. 

3) Understanding data structure and algorithms-

Now it’s time for the next challenge, learning the data structure. In informal terms, learning data structure and algorithms is like learning the grammar to speak the language. It sets the rules for effective communication in data-ways. For beginners, it’s primary to understand the algorithms and how the inputs respond to commands. Basic knowledge about what are variables, strings, lists, tuples, and the dictionary is the best way to begin. Try python exercises with solutions, it gives you a practical tour of how and why for using algorithms.

4) How to lookup for data If you are a beginner, what you do not know is how to read or write files with your preferred coding languages. Before jumping into that, you need to understand what are file formats and why it is important. We are quite familiar with filenames ending with ‘txt’ or ‘xls’ or ‘jpg’ and we can immediately identify whether it’s a word document or a spreadsheet. Similarly, AI programmers use file ‘csv’ or ‘HDF5’ or ‘netCDF’ to train and work on multiple data sets as it is easily comprehended by the systems. Hence, having a basic understanding of the types of file formats will help you to extract, read and work with data sets retrieved from open sources and libraries. 

5) Visiting coding libraries

Unlike the usual one, coding libraries contain a hefty number of reusable codes or algorithms that come in handy for completing your coding assignments. Here you will get hands-on power modules that suit the purpose of developing the program. As python is the primer driver in the AI-ML space, knowing the purposes of the python libraries like Numpy, Pandas, Matplotlib, and Scikit-Learn can be a good starting point. 

Following are the 5 steps warm-up before you set-off as a pro-learner. If you aspire to boost your career prospects and learn AI-ML applications, IIT Mandi and Wiley offer PG Certification in Applied AI and ML. This course will walk you through Deep AI processing and industry-specific tools for the entire AI lifecycle. You can learn modeling user-friendly APIs with tools like Python, Keras, Tensorflow, NLTK, NumPy, Scikit-learn, Pandas, Jupyter, and Matplotlib. 

Plus you will learn to 'Apply AI' in real-world scenarios under the guidance of the top industry experts organized by the Wiley Innovation Advisory Council. 

For over 200 years, Wiley has been helping people and organizations develop the skills and knowledge they need to succeed. They are dedicated to developing efficient learning products, digital transformation education, learning, assessment, and certification solutions to help universities, businesses, and individuals move between education and employment and achieve their ambitions. In 2020, WileyNXT has been recognized by Fast Company for its outstanding innovations in education. 

Miles Education, always committed to your career success brings to you new-age certifications in Finance and Emerging Technologies. We have partnered with IIT Roorkee, IIT Mandi, IIM Lucknow, IIM Kozhikode, and WileyNXT to present PG certifications in AI, ML, Deep Learning, and Analytics. 

To know more and to apply visit Miles Education today.

[classbazaar]

Top Free Online Courses for Skill Development | Class Bazaar

In today's fast-paced digital world, learning has never been more accessible. With the rise of free online courses, anyone with an internet connection can now acquire new skills, deepen their knowledge, and even change their career path—all without spending a dime. Whether you're looking to improve your professional expertise, explore a new hobby, or simply quench your thirst for knowledge, free online courses are a powerful tool for self-improvement.

Why Choose Free Online Courses?

Free online courses offer an unparalleled opportunity for individuals to learn without the financial burden of traditional education. They are ideal for:

Career Advancement: Many free courses are designed by industry experts and prestigious institutions, offering skills that are directly applicable to your career.

Personal Development: From language learning to creative arts, you can explore a wide range of subjects that interest you.

Flexibility: Learn at your own pace, on your own schedule, and from the comfort of your home.

Accessibility: With just a device and internet connection, quality education is available to everyone, regardless of geographic location or financial status.

Popular Platforms Offering Free Online Courses

Several online platforms provide a vast selection of free courses across various disciplines. Some of the most popular platforms include:

Coursera: Partnering with top universities and organizations, Coursera offers free courses in fields such as business, technology, and humanities.

edX: Founded by Harvard and MIT, edX provides access to high-quality courses from leading institutions worldwide.

Udemy: Udemy's extensive library includes thousands of free courses on topics ranging from programming to personal development.

Khan Academy: Best known for its focus on K-12 education, Khan Academy also offers free courses in subjects like math, science, and economics.

How to Get the Most Out of Free Online Courses

To maximize the benefits of free online courses, it's essential to approach them with the right mindset and strategies. Here are some tips to help you succeed:

Set Clear Goals: Before starting a course, determine what you want to achieve. Whether it's mastering a new skill or gaining a certificate, having a clear goal will keep you motivated.

Create a Study Schedule: Allocate specific times during your week to study. Consistency is key to making progress.

Engage Actively: Take notes, participate in discussion forums, and complete assignments to reinforce your learning.

Practice Regularly: Apply what you've learned in real-life scenarios or through practice exercises to solidify your understanding.

Stay Committed: Free courses often require self-discipline. Stay committed to your learning journey, even when it gets challenging.

Top Categories of Free Online Courses

Free online courses are available in virtually every subject imaginable. Some of the top categories include:

1. Technology and Programming

In the ever-evolving tech world, staying updated with the latest skills is crucial. Free courses in this category cover everything from coding languages like Python and Java to data science, cybersecurity, and artificial intelligence.

2. Business and Management

For aspiring entrepreneurs or those looking to climb the corporate ladder, free courses in business strategy, leadership, marketing, and project management are invaluable.

3. Personal Development and Wellness

This category includes courses on mindfulness, mental health, time management, and more, helping you lead a balanced and fulfilling life.

4. Creative Arts

Explore your artistic side with free courses in photography, writing, graphic design, music, and other creative fields.

5. Languages

Learning a new language opens doors to new cultures and opportunities. Free language courses are available for everything from Spanish and French to less commonly taught languages like Korean or Swahili.

Benefits of Free Online Courses

Free online courses come with numerous benefits that make them an attractive option for learners of all ages:

Cost-Efficiency: As the name suggests, these courses are free, making education accessible to everyone, regardless of their financial situation.

Diverse Learning Opportunities: With courses available in a wide range of subjects, learners can explore new interests or deepen their expertise in specific areas.

Certificates of Completion: Many platforms offer certificates for free courses, which can be a valuable addition to your resume or LinkedIn profile.

Global Community: Online courses connect you with learners from around the world, providing a rich, multicultural learning experience.

Challenges of Free Online Courses

While free online courses offer many advantages, there are also some challenges to consider:

Lack of Structure: Without a set schedule or deadlines, it can be easy to procrastinate or lose focus.

Limited Interaction: Free courses may not offer the same level of interaction with instructors or peers as paid courses or traditional classrooms.

Certificate Fees: While the course content is free, some platforms may charge a fee for official certificates.

How to Choose the Right Free Online Course

Selecting the right course can be overwhelming, given the vast number of options available. Here’s how to make an informed decision:

Research the Course: Look for reviews, ratings, and testimonials from other learners.

Check the Syllabus: Ensure the course content aligns with your learning goals.

Assess the Instructor’s Credentials: Opt for courses taught by experienced professionals or institutions.

Consider the Course Length: Choose a course that fits your schedule, whether you prefer a short, intensive course or a more extended program.

Start Your Learning Journey Today

The world of free online courses is vast and full of potential. Whether you're a student, a professional, or a lifelong learner, there's something for everyone. At Class Bazaar, we curate the best free online courses across various platforms and disciplines, making it easier for you to find the right course to match your goals.

Ready to unlock new opportunities? Explore our free online courses and start learning today!

[theinjectlikes2]

Intro to Python - Whiteboard Friday

Posted by BritneyMuller

Python is a programming language that can help you uncover incredible SEO insights and save you time by automating time-consuming tasks. But for those who haven't explored this side of search, it can be intimidating. In this episode of Whiteboard Friday, Britney Muller and a true python expert named Pumpkin offer an intro into a helpful tool that's worth your time to learn.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Hey, Moz fans. Welcome to another edition of Whiteboard Friday. Today we're talking all about introduction to Python, which is why I have a special co-host here. She is a ball python herself, total expert. Her name is Pumpkin, and she's the best. 

What is Python?

So what is Python? This has been in the industry a lot lately. There's a lot of commotion that you should know how to use it or know how to talk about it. Python is an open source, object-oriented programming language that was created in 1991.

Simpler to use than R

Some fun facts about Python is it's often compared to R, but it's arguably more simple to use. The syntax just oftentimes feels more simple and common-sense, like when you're new to programming. 

Big companies use it

Huge companies use it. NASA, Google, tons of companies out there use it because it's widely supported.

It's open source

It is open source. So pretty cool. While we're going through this Whiteboard Friday, I would love it if we would do a little Python programming today. So I'm just going to ask that you also visit this in another tab, python.org/downloads. Download the version for your computer and we'll get back to that. 

Why does Python matter?

So why should you care? 

Automates time-consuming tasks

Python is incredibly powerful because it helps you automate time-consuming tasks. It can do these things at scale so that you can free up your time to work on higher-level thinking, to work on more strategy. It's really, really exciting where these things are going. 

Log file analysis

Some examples of that are things like log file analysis. Imagine if you could just set up an automated system with Python to alert you any time one of your primary pages wasn't being crawled as frequently as it typically is. You can do all sorts of things. Let's say Google crawls your robots.txt and it throws out a server error, which many of you know causes huge problems. It can alert you. You can set up scripts like that to do really comprehensive tasks. 

Internal link analysis

Some other examples, internal link analysis, it can do a really great job of that. 

Discover keyword opportunities

It can help you discover keyword opportunities by looking at bulk keyword data and identifying some really important indicators. 

Image optimization

It's really great for things like image optimization. It can auto tag and alt text images. It can do really powerful things there. 

Scrape websites

It can also scrape the websites that you're working with to do really high volume tasks. 

Google Search Console data analysis

It can also pull Google Search Console data and do analysis on those types of things.

I do have a list of all of the individuals within SEO who are currently doing really, really powerful things with Python. I highly suggest you check out some of Hamlet Batista's recent scripts where he's using Python to do all sorts of really cool SEO tasks. 

How do you run Python?

What does this even look like? So you've hopefully downloaded Python as a programming language on your computer. But now you need to run it somewhere. Where does that live? 

Set up a virtual environment using Terminal

So first you should be setting up a virtual environment. But for the purpose of these examples, I'm just going to ask that you pull up your terminal application.

It looks like this. You could also be running Python within something like Jupyter Notebook or Google Colab. But just pull up your terminal and let's check and make sure that you've downloaded Python properly. 

Check to make sure you've downloaded Python properly

So the first thing that you do is you open up the terminal and just type in "python --version." You should see a readout of the version that you downloaded for your computer. That's awesome. 

Activate Python and perform basic tasks

So now we're just going to activate Python and do some really basic tasks. So just type in "python" and hit Enter. You should hopefully see these three arrow things within your terminal. From here, you can do something like print ("Hello, World!"). So you enter it exactly like you see it here, hit Enter, and it will say "Hello, World!" which is pretty cool.



You can also do fun things like just basic math. You can add two numbers together using something like this. So these are individual lines. After you complete the print (sum), you'll see the readout of the sum of those two numbers. You can randomly generate numbers. I realize these aren't direct SEO applications, but these are the silly things that give you confidence to run programs like what Hamlet talks about.

Have fun — try creating a random number generator

So I highly suggest you just have fun, create a little random number generator, which is really cool. Mine is pulling random numbers from 0 to 100. You can do 0 to 10 or whatever you'd like. A fun fact, after you hit Enter and you see that random number, if you want to continue, using your up arrow will pull up the last command within your terminal.

It even goes back to these other ones. So that's a really quick way to rerun something like a random number generator. You can just crank out a bunch of them if you want for some reason. 

Automating different tasks

This is where you can start to get into really cool scripts as well for pulling URLs using Requests HTML. Then you can pull unique information from web pages.

You can pull at bulk tens of thousands of title tags within a URL list. You can pull things like H1s, canonicals, all sorts of things, and this makes it incredibly easy to do it at scale. One of my favorite ways to pull things from URLs is using xpath within Python.

This is a lot easier than it looks. So this might be an xpath for some websites, but websites are marked up differently. So when you're trying to pull something from a particular site, you can right-click into Chrome Developer Tools. Within Chrome Developer Tools, you can right-click what it is that you're trying to scrape with Python.

You just select "Copy xpath," and it will give you the exact xpath for that website, which is kind of a fun trick if you're getting into some of this stuff. 

Libraries

What are libraries? How do we make this stuff more and more powerful? Python is really strong on its own, but what makes it even stronger are these libraries or packages which are add-ons that do incredible things.

This is just a small percentage of libraries that can do things like data collection, cleaning, visualization, processing, and deployment. One of my favorite ways to get some of the more popular packages is just to download Anaconda, because it comes with all of these commonly used, most popular packages.

So it's kind of a nice way to get all of it in one spot or at least most of them. 

Learn more

So you've kind of dipped your toes and you kind of understand what Python is and what people are using it for. Where can you learn more? How can you start? Well, Codecademy has a really great Python course, as well as Google, Kaggle, and even the Python.org website have some really great resources that you can check out.

This is a list of individuals I really admire in the SEO space, who are doing incredible work with Python and have all inspired me in different ways. So definitely keep an eye on what they are up to:

Hamlet Batista

Ruth Everett

Tom Donahue

Kristin Tynski

Paul Shapiro

Tyler Reardon

JR Oakes

Hulya Coban

@Jessthebp

But yeah, Pumpkin and I have really enjoyed this, and we hope you did too. So thank you so much for joining us for this special edition of Whiteboard Friday. We will see you soon. Bye, guys.

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