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Best Online Data Science Course 2025: Learn at Pro Academys
Best Online Data Science Courses for Career At Pro Academys

In today’s digital age, Pro Academys data science has emerged as one of the most sought-after career paths. Whether you are a beginner looking to break into the field or a professional seeking to upgrade your skills, finding the Pro Academys best online course for data science is essential. With a variety of options available, selecting the right program that covers topics like machine learning, data analytics, data mining, Python, SQL, artificial intelligence, and statistical analysis can be overwhelming. This guide will help you explore the Pro Academys top data science courses online, the skills you need, and how to build a successful career in this field.
Why Choose Pro Academys Best Online Data Science Course as a Career?
The demand for data scientists, data analysts, and data engineers is skyrocketing across industries. Companies rely on data analysis, predictive analytics, and business intelligence to make data-driven decisions. According to reports, the job market for Pro Academys data science professionals will continue to expand through 2025, making it one of the most lucrative career options today.
What Makes a Great Pro Academys Data Science Course?
A high-quality Pro Academys data science program should provide hands-on learning, exploratory data analysis, and knowledge of statistical modeling. The Pro Academys best online courses will cover:
Fundamentals of Data Science – Introduction to data structures, data manipulation, and data storage.
Programming Skills – Mastering Python, R programming, and SQL.
Machine Learning and AI – Learning applied machine learning, deep learning, and neural networks.
Data Visualization – Using tools like Tableau and TensorFlow to analyze data.
Business Analytics – Understanding business intelligence and insights from data.
Statistical Analysis & Probability Theory – Essential for building predictive models.
Top Online Pro Academys Data Science Courses
Here are some of the Pro Academys best data science courses online that offer comprehensive training:
1. Coursera – Pro Academys Data Science Specialization by Johns Hopkins University
Covers Pro Academys data science in Python, regression analysis, and exploratory data analysis.
Hands-on projects to analyze large amounts of data.
2. edX – MicroMasters in Pro Academys Data Science by UC San Diego
Ideal for those who don’t have a bachelor’s degree in data science.
Covers unstructured data, relational databases, and statistical modeling.
3. Udacity – Pro Academys Data Scientist Nanodegree
Focus on predictive analytics, deep learning, and natural language processing.
Provides real-world data science projects.
4. IBM Pro Academys Data Science Professional Certificate on Coursera
Covers machine learning in Python, SQL, and BI tools.
Suitable for all various skill levels, from beginner to advanced.
5. Harvard Online Pro Academys Data Science Certificate (HarvardX)
Covers mathematics and statistics, data manipulation, and probability theory.
Includes hands-on learning and projects.
Essential Skills for a Pro Academys Data Scientist
To become a successful Pro Academys data scientist, you need to master:
Programming – Proficiency in Python, R, and SQL.
Data Analysis & Visualization – Expertise in Tableau, TensorFlow, and data visualization techniques.
Statistical Knowledge – Understanding regression, probability, and predictive analytics.
Machine Learning & AI – Applying algorithms, deep learning, and analytical skills.
Business Intelligence – Knowledge of BI, relational databases, and Google Data tools.
Hands-On Learning & Real-World Projects
A good Pro Academys online data science degree or training program should offer hands-on learning through projects on data sets. Working on real-world projects helps develop analytical skills, structured query language (SQL) proficiency, and insights from data.
Pro Academys Data Science Career Opportunities
After completing a Pro Academys data science training program, you can explore careers as:
Pro Academys Data Analyst – Specializing in data visualization, structured query language, and business analytics.
Pro Academys Data Engineer – Managing complex data, data storage, and relational databases.
Pro Academys Machine Learning Engineer – Developing predictive analytics and AI models.
Pro Academys BI Analyst – Enhancing business intelligence with statistical modeling.
How to Choose the Right Pro Academys Course?
When selecting the Pro Academys best online course for data science, consider:
Course Content – Does it cover Pro Academys data science in Python, machine learning, and AI?
Flexibility – Is it self-paced or instructor-led?
Hands-on Learning – Are there projects involving big data and data manipulation?
Certification – Will it boost your career in Pro Academys data science?
Cost – Does it offer free Pro Academys data science courses or affordable plans?
Conclusion
Investing in a Pro Academys data science online course is the first step toward a successful career. Whether you are a beginner or an experienced professional, the right course will provide you with the skills in Pro Academys data science, machine learning, and business intelligence. Choose wisely, apply hands-on learning, and start your journey in Pro Academys data science and analytics today!
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Top Python Development Company San Diego
SynergyTop is the Top Python Development Company in San Diego. We offer Futuristic Python Web Development Services in San Diego & Los Angeles.
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You must be aware that PostgreSQL is the most reliable and advanced open-source database. However, using the database for small, medium, or large enterprises can prove to be a hassle. For PostgreSQL to work efficiently, one needs a team of professionals who can support and protect your business. If you are looking for an expert team that can combine the performance of PostgreSQL, Django, and Python web development Company in San Diego, well, you have landed at the right place!
#python web development Company in san diego#Python web development Company#Top Python web development Company#Python web development
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Online Education and Coding: 5 Websites to Learn Coding for Free
The following is a guest post by Colin Simpson, a project management professional with experience in the IT industry. If you would like to submit a guest post, please contact us.
“Coding is not for everyone!” Said no one ever in the modern world. Gone are the days when coding was considered to be only for a few nerds who could spend endless hours in front of a computer screen. Today, coding is a fundamental life skill that helps freelancers, marketers, and entrepreneurs excel at what they are doing.
Coding for yourself is empowering. It allows you to transform your idea into reality. If you are a blogger, coding can help you create an intuitive blog. If you are an entrepreneur, coding can help you with your product idea. Also, coding is one of the popular Education Trends that will Shape the 2019-2020 Academic Year.
Why should you learn to code?
You must be thinking, why learn to code when there are programmers you can hire?
Well, when you code for yourself, you can reduce your dependence on others and execute your idea exactly like it is in your head. The added cost advantage can be a cherry on the top.
For many of us, having the basic programming knowledge will mean that any developer cannot fool you into thinking that an idea is impossible to convert into a program. When you know how to code, you can work on your vision without relying on anyone else.
Why are online methods a great way to learn coding?
The internet has been a great facilitator and has changed every aspect of our life- from shopping to entertainment. Similarly, when we think of education, online learning has completely revolutionized the domain. Anyone can learn using the internet without thinking about the distance, time or language barrier.
When we think of coding, there cannot be a better way to learn coding than the internet. For the instructors too, teaching coding via the internet is really easy. They can provide real-time support and relatable examples by using technology and connectivity, without any trouble of setting up and maintaining physical infrastructure. This way, a lot of resources and time get saved and teachers can concentrate on teaching, instead of other aspects.
Many companies prefer hiring developers who have learned programming on their own or via online learning. We also prefer such candidates and it helped us to become the top app development company in San Diego.
5 Websites to Learn Coding for Free
In the age of the internet, all you need to learn coding is just a reliable internet connection and a laptop. The rest you can discover and try on your own. Here are 5 amazing resources you can use to learn coding without spending even a single penny:
1. Code.org
One of the biggest coding resources on the internet, the website offers detailed guides and tutorials on how to code.
Code.org is really popular among amateur coders and aspirants who want to learn coding. This is because of the presence of several tutorials, applications and guides that are offered by Code.org partners, making the website a large repository of learning resources. Being a non-profit initiative, code.org aims to promote the concept of code learning among school and college-going children.
One can learn how to develop games for school children, JavaScript programming and a lot of other exciting things.
Apart from self-paced tutorials, the website also conducts specific lessons in the form of lectures by famous programmers and instructors for easy learning.
2. Codeacademy
Codeacademy has been used by more than 45 million people all over the globe to learn coding. An educational company that believes in making programming more engaging, Codeacademy offers useful courses in HTML, CSS, SQL, JavaScript, C++, Python, among other courses.
One can learn several technical aspects associated with coding through self-paced courses on a wide range of programming languages.
3. MIT Open Courseware
MIT Open Courseware is ideal for someone who has already cleared the basic stages and wants to learn advanced concepts. An initiative of Massachusetts Institute of Technology, Open Courseware gives you a chance to take up language-specific courses on C++, MatLab, Java and other programming languages.
One can also learn more about programming concepts and other innovative technologies using the Open Courseware website.
4. Khan Academy
Khan Academy was developed by an educator, Salman Khan in 2006 and is one of the most genuine free eLearning platforms. There are several dedicated courses and video tutorials on the platform that can help you in learning how to code, how to create webpages with HTML, CSS.
A special program on the website, ‘Hour of Code’ also teaches students more about computer science and programming.
Students can share their learnings with other students and this kind of shared learning model creates more engagement. Apart from instructor-led courses, there are several specialized courses and learning material that you can utilize to create your own extensive code learning repository.
5. Web Fundamentals
A project by Google for web developers, Web Fundamentals has a large number of free resources like tutorials, guides and walkthroughs to learn the nuances of HTML5 coding. Being an open-source platform, one can use the HTML5 code to learn several aspects of advanced coding and programming.
Recommended for someone with basic programming knowledge, this website can serve as a useful resource if you want to refine your skills, grow as a programmer and achieve bigger things with your coding knowledge.
Wrapping Up
Learning to code is no longer an expensive ordeal. The online medium is quite an affordable way to learn coding. Anyone from a school-going kid to an adult can grasp coding fundamentals and use them to his/her benefit by learning to code online. Coding can be especially a useful skill if you plan to launch your own startup or wish to make a career in the STEM industry.
As it is said, a little extra knowledge is never harmful. So, you should not shy away from donning your learning hats and start learning to code, right away!
Author’s Bio: Colin Simpson is a competent project management professional with rich experience in the IT industry. He is currently working as a project manager at BlueKite Apps. Over the years, he has worked with startups and business owners to transform their ideas into digital solutions, and that experience has helped him to start writing on various aspects of the IT industry. You can find Colin on LinkedIn at: https://www.linkedin.com/in/iamcolinsimpson/
Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply an endorsement, recommendation, or favoring by Touro College.
The post Online Education and Coding: 5 Websites to Learn Coding for Free appeared first on Online Education Blog of Touro College.
Online Education and Coding: 5 Websites to Learn Coding for Free published first on https://medium.com/@DLBusinessNow
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Car Security San Diego
While many add-on purchases for automobiles are very popular, probably the most significant addition for any vehicle is a protection car alarm. With higher than a million vehicles stolen each year, taking proactive steps to work against the chance of theft is just wise practice for several car owners. It stands to reason that the car owner would want to protect this kind of huge financial investment. Apart from your property, your car is one of the most expensive thing you own. Doesn't it sound right to take care of it? Taking care of your car goes beyond changing the oil and keeping it clean. Really taking care of your car involves doing everything you are able to to keep it from being stolen.
Car Video San Diego serve as an affordable and effective method to stop you and your car from becoming the next car theft victims.
As a car owner, it is in your best interest to investigate security car alarms to find the best protection system for both your vehicle and your budget. If you believe you can't afford a car alarm system, consider if you can afford for your car to be stolen. That important question can put the minimal cost of a good alarm system in perspective.
What Are The Options?
There's a tremendous variety of choices when it comes to choosing a great car alarm. There are lots of different manufacturers, models and technological features for security car alarms. Just about any budget may be accommodated with a protection car alarm. Probably the most economical model is not at all times the best choice for your vehicle's protection, though. Often just investing several more dollars to obtain a high quality system can have an enormous effect on the entire effectiveness of the security car alarm system you choose.
Directed Electronics is definitely an Industry Leader
Directed Electronics is one of the very most established and best known names in security car alarms. This respected and respected company is accountable for the two top security alarm brands, Python and Viper. The business's product mix also incorporates products from other major brands that have become an integral part of their organization, including Avital, Clifford, Autostart and AutoCommand. With more than two decades in the security car alarm industry, the company's experience is actually depicted by its impressive portfolio of vehicle security products.

Pick a Top Brand
Whether you select a Directed Electronics product, or one from an alternative firm, it is a good idea to decide on your unit from among the industry's top brands. Working together with industry leaders helps to guarantee the highest quality and most advanced electronics technologies for your security car alarm. You merely want to get a car alarm from a respected company that specializes in vehicle security to make sure that the body has the most recent technology. Developing the ability to discern the major brands of vehicle security products can help you make perfect choices in automotive protection.
One of the very most respected security car alarm brands is Viper. Viper is often the machine of choice for discerning expert drivers. Such discriminating consumers understand the value of a first-rate alarm system due to the superior technologies employed to keep your vehicle constantly protected. Python is another great name in car security alarms, well-known for its unique technologies that include recognized names like Revenger, Failsafe, Stinger, Starter Kill and DoubleGuard. The Phython and Viper security alarm systems are focused on user convenience paired with extreme vehicle protection systems. It doesn't get much better than that.
Window Tinting San Diego is another respected brand. It's been protecting vehicles for more than two decades, and has kept up with with technological advances like the MATRIX and G5 Technologies. These systems have the ability to instantly intimidate potential car thieves, which can be crucial for maximum protection of our car.
Avital has already been around more than 2 full decades with security car alarm products which can be trusted by many, many consumers. Avital features a reputation for providing both outstanding security and remote starter systems.
They are not the only first-rate choices for alarm systems. You will find amount of other reputable products that will meet your needs. Other top brands for security car alarms include Hornet, Valet, Ready Remote and AutoCommand, Astroflex, Automate Securit, and Autostart. Also, Merlin systems is a strong selection for motorcycle protection options. The benefits of security car alarm systems are greatly enhanced whenever you select yous from among these leading industry brands. It only is sensible to stick with recognized experts in security when protecting your own vehicle. The experience and expertise of top brand car alarm systems is the better tool for keeping your vehicle best protected from the threat of robbery.
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10 Courses for Freelancers
Upwork released a study that covers the top 20 fastest growing skills for freelancers. Number one on the list is Blockchain, followed by TensorFlow, Machine Learning, Information Security, and more. We’ve rounded up 10 courses that cover a few of the in-demand topics freelancers search for so you can start upskilling today:
1. Learning How to Learn: Powerful mental tools to help you master tough subjects – University of California San Diego
This course gives you easy access to the invaluable learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. You’ll learn about the how the brain uses two very different learning modes and how it encapsulates (“chunks”) of information. No matter what your skill levels in topics you would like to master, you can change your thinking and change your life.
2. Machine Learning with TensorFlow on Google Cloud Platform Specialization – Google Cloud
Learn how to write distributed machine learning models that scale in TensorFlow, scale out the training of those models and offer high-performance predictions. You will experiment with end-to-end Machine Learning (ML), starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud Platform.
3. Blockchain Specialization – The State University of New York & The University at Buffalo
This specialization introduces blockchain and will prepare you to program on the Ethereum blockchain. The four courses will provide you with an understanding and working knowledge of foundational blockchain concepts, a skill set for designing and implementing smart contracts, methods for developing decentralized applications on the blockchain, and information about the ongoing specific industry-wide blockchain frameworks.
4. Getting started with Augmented Reality – Institut Mines-Télécom
This course will teach you the basics of developing mobile applications using Mixed and Augmented Reality (MAR) technologies. Through hands-on projects, you’ll learn practical techniques to rapidly and easily prototype three different applications for Android smartphones and tablets – even with no previous coding experience. Whatever your background, you’ll learn how to design cutting-edge visual experiences that will enhance your job prospects.
5. Information Security: Context and Introduction – University of London
In this course you will explore information security through some introductory material and gain an appreciation of the scope and context around the subject. This includes a brief introduction to cryptography, security management and network and computer security that allows you to begin the journey into the study of information security and develop your appreciation of some key information security concepts.
6. Python for Everybody Specialization – University of Michigan
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
7. Functional Programming in Scala Specialization – Ecole Polytechnique Fédérale de Lausanne
Discover how to write elegant code that works the first time it is run. This Specialization provides a hands-on introduction to functional programming using the widespread programming language, Scala. A final capstone project will allow you to apply the skills you learned by building a large data-intensive application using real-world data.
8. Digital Marketing Specialization – University of Illinois at Urbana–Champaign
Master strategic marketing concepts and tools to address brand communication in a digital world. You’ll learn about several aspects of the new digital marketing environment, including topics such as digital marketing analytics, search engine optimization, social media marketing, and 3D Printing.
9. Fundamentals of Graphic Design – California Institute of the Arts
This course will teach you the fundamental principles of graphic design: image making, typography, composition, and working with color and shape. These are foundational skills that are common in all areas of graphic design. This course will offer you lots of opportunities to get your hands dirty with exercises and with practical projects.
10. Successful Negotiation: Essential Strategies and Skills – University of Michigan
Negotiation is the key to business success. No business can survive without profitable contracts and within a company, negotiation skills can lead to your career advancement. In this course, you’ll learn to plan a negotiation strategy, key tactics for success, and how to create a contract.
The post 10 Courses for Freelancers appeared first on Coursera Blog.
10 Courses for Freelancers published first on https://medium.com/@GetNewDLBusiness
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6 Online Resources That Will Help You Understand Artificial Intelligence Better By Kelechi Udoagwu
geralt / Pixabay
Artificial Intelligence (AI) used to be just a Sci-Fi concept, something that only existed in movies, books, and pop culture. But as technology developed and human capacity evolved with it, we have been able to design artificially intelligent machines, machines that mirror human behaviour and learn new concepts just the way we can.
For many people, artificial intelligence is still an alien, abstract idea. They do not understand how it works or why it is important. For others, it piques their curiosity, but they just have not found the right materials that will acquaint them with the subject.
To help solve these problems, I have compiled a list of seven free resources that will help you (and anyone else who’s interested) understand Artificial Intelligence better.
These resources are curated from the top universities and companies around the world doing remarkable things with in the field. The materials range from simple, easy-to-consume guides to more intricate courses. All of which are online and you can learn at you own pace.
Here you go. Thank me later.
A Beginner’s Guide to AI/ML by Vishal Maini
This Medium post is a resource that provides a roadmap for both technical and non-technical people who want to better understand Machine Learning. It covers basic concepts in probability, statistics, programming, linear algebra, and calculus.
The post is written by Vishal Maini, a research content manager at DeepMind, former head of growth at Upstart and an alumnus of Yale University. He is someone who isn’t just knowledgeable about the topic, but has also worked in the space for years and knows the in-and-outs.
Google Machine Learning resources
“Whether you’re just learning to code or you’re a seasoned machine learning practitioner, you’ll find information and exercises to help you develop your skills and advance your projects” – This is how Google sells this course. Through the program, you will learn from machine learning experts at Google, the people who have built some of the most mind-blowing artificially intelligent features.
Google lets you filter down the resources available to on this platform, whether you’re a business decision maker, just a curious person, a data scientist, a researcher, a software engineer, or a student. The program includes courses, tutorials, videos, documents, etc.
Artificial Intelligence by Columbia University
This Artificial Intelligence course designed by Columbia University is aimed at improving your practical knowledge of the subject. The course seeks to answer the question: How can I apply Artificial Intelligence to everyday life?
Apart from introducing you to basic AI concepts, the course will take you through the history of AI and give you a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.
Machine Learning Fundamentals by UC San Diego
This course designed by the University of California, San Diego helps you understand the role machine learning plays role in data-driven modelling, prediction, and decision-making. It arms you with the knowledge of different types of data analysis.
It uses real-world case studies to teach you how to classify images, identify salient topics in a mass of documents, partition people according to their personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.
Machine Learning by Stanford University
This Machine Learning course takes you deeper into the world of AI. It is taught by Andrew Ng, Co-founder, Coursera, Adjunct Professor at Stanford University and former head of Baidu AI Group/Google Brain.
It introduces you to the idea of teaching a computer how to learn concepts, then it dives deeper into Linear Regression, Logistic Regression, and Neural Networks.
Applied AI with DeepLearning by IBM
This is a 4-week course that takes you into the deep end of Artificial Intelligence. It is part of the IBM Advanced Data Science Certificate. To take this course, because of its advanced nature, you will require some coding skills, especially python, but other languages are acceptable too.
Although artificial intelligence is a new concept, you do not have feel overwhelmed by the subject. Using the resources above and others you can find with a simple Google search.
We are just in the beginning of our this revolution changing the way we live, work, communicate and do most things.
The journey to understanding artificial intelligence in its entirety is long, but taking the first step will get you there, make you more valuable in the job market or put your company ahead of the competition. looking at all these resources, you quickly find that it is an exciting trip to take.
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The news adheres to information Equifax had cannot successfully set up a patch for a security vulnerability hackers later utilized to swipe client details. The 650-year-old city is the historical funding of the highland area of Podhale 1, which stretches between the Gorce Mountains on the north, and also Tatra Mountains on the south. Marquis WILL NOT ELIMINATE COCCIDIA, only AVOID it from surge development as a result of STRESS AND ANXIETY. Individuals marched around the center to recognize people shed by suicide. A company may designate a Trainee NTE to a various setting, however initially the company has to provide minimal public alert (internal to the firm - not on USAJOBS) to similarly located agency Trainees who may additionally have an interest in the Trainee setting. The name Podhale essentially converts as „ below the hill glen" in English. 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5 Ways to Get Started with Machine Learning
Machine learning has taken off and it’s doing so with fury, bringing new insights to every single industry. If you want to be in demand, this is a skill that will put you in the front line. As intimidating as it may seem, it’s surprisingly easy if you approach it the right way.
Machine learning (ML) is a fascinating practice and field of study. It's what allowed the introduction of self-driven cars, of robots that can clean your house, the navigation system of drones of all kinds, the recommendation system behind YouTube and Netflix, face recognition systems, hand written recognition, game playing, and lots more.
And because of its incredibly high value and somewhat cryptic nature, it's an expertise in very high demand that keeps expanding to different areas --- which just five years ago would have seemed inconceivable. Through this article, we'll see different practical ways to approach it.
"Pardon Me … but What is Machine Learning?"
ML is a branch of artificial intelligence (AI). As Arthur Samuel --- one of the pioneers in the field --- put it, ML gives "computers the ability to learn without being explicitly programmed". That is, instead of programming a computer (or robot) to do something, you give information and set the framework to let the system program itself.
Freaking fascinating? Yes, but we won't get into the details of this seemingly impossible thing here, but instead point you to the right places where you'll be able to find that for yourself.
Before Starting, a Word of Caution
ML is something of an advanced practice, and you'll need to have not only some foundations in computer sciences, but also be able to code in at least one programming language. Some popular programming languages for ML are Python, R, Java, C, and MATLAB, among others.
1. Start Very Quickly … Like, Really, in Less than Ten Minutes
Sometimes, and for some people, it's better to just get hands on into something to have a first taste and develop an intuition of what this new art or skill is about, and then dig deeper into some specifics and details.
Google's Machine Learning Recipes with Josh Gordon is just that --- a straightforward and practical approach to ML. Using the Python scikit-learn and TensorFlow libraries, Josh will walk you through very practical examples and down-to-earth explanations behind the very principles of ML.
Here's the first 7-minute video of the series, introducing a supervised learning algorithm in Python --- in just six lines of code!:
The publishing schedule is somewhat irregular, with videos published every month or second month, covering topics such as decision trees, feature selection, pipelines, classifiers: not bad at all for 6-to-8 minute videos that anyone with a little foundation in programming can follow.
2. Take Courses from Top-Notch Universities, for Free
If you're hungry for quality knowledge, you may have heard by now about Coursera, edX, Udacity, and many, many others. We're talking MOOCs, or massive open online courses.
Let's break it down quickly:
massive: they have no vacancy limits, and can be accessed by as many people as desired.
open: anyone can access them, regardless of their age and previous knowledge on the topic, and independently if they're able to pay for a certification or not.
online: all you need is a device connected to the Internet; even a mobile phone would do.
course: these are actual courses with reading materials, practical exercises, and even deadlines.
Let's see some courses you could start with.
Stanford's Andrew Ng Machine Learning
Stanford Prof. Ng is a leading researcher on the field of artificial intelligence, and is the person who pretty much started the MOOC spark that would later turn into a fire of knowledge when he first put his Machine Learning online course. The response was overwhelming, with many thousands of people from all around the world taking the course and discussing this topic. He later turned this course into what it is today Coursera, the leading provider of MOOCs.
The course is as fabulous as it is challenging. I remember having spent an hour or so just to read a 5-page assignment scope before I was able to grasp it. So unlike Josh Gordon's series, this is a little more on the academic side, but with a lot of practical knowledge and advice that will be very useful later on in your ML practices. But it is doable, and the amount of feedback on the forums is truly overwhelming. Mind you, it was among the first MOOCs I ever took, and one of the best.
Course details:
Approx. duration: 2–5 months
Difficulty: high
Workload: mid-to-heavy
Sebastian Thrun's Intro to Artificial Intelligence
Also a professor and AI researcher at Stanford (on the field of robotics), co-founder of Google X Lab (the "semi-secret" R&D company behind of Google's self-driven cars, among other projects), Sebastian is also the founder of a mayor MOOC provider, Udacity. Along with Peter Norvig (Director of Research at Google), he put together the amazing Intro to Artificial Intelligence.
This is pretty much the foundation to all things ML. It's a lot lighter than Andrew's course, with its content spread over more units to make it easier to digest, though it's a long one.
Course details:
Approx. duration: 4 months
Difficulty: intermediate
Workload: light
Caltec's Yaser S. Abu-Mostafa Learning from Data
Prof. Yaser is another of the pioneers of putting quality learning material online, making available his Learning from Data ML course on his website, with all of its lectures, learning materials and exams, even before MOOCs were a thing. Later he would package these materials into a MOOC offered regularly by Caltech on edX.
I took this one as well, and I can tell you that you'll have to do some heavy lifting here. But if you've enjoyed Andrew's course and are hungry for more foundations, this seems like a reasonable next step.
Course details:
Approx. duration: 4 months
Difficulty: very high
Workload: very heavy (10–20 hours per week)
Other Coursera, edX and Udacity Courses
There's a very extensive offering of ML and AI courses that you can take for free, not only at Coursera, edX, and Udacity, but at other MOOC providers as well, such as Data Camp --- though data science seems to be something of a niche for the three providers we've discussed.
3. Get Certified Education, for a Fraction of the Price
So far, we've talked free MOOCs. They're awesome, and you don't need to pay a cent to enroll in them and start learning. In the beginning, these providers used to offer free certificates or statements of accomplishments, even some of them verifiable online. These programs, however, have been discontinued, so in most cases you won't get a certificate or any type of credential that you could use to demonstrate your education to a potential employer, or even to another higher education institution.
This may not be a problem if you just want to learn for the sake of it, and even use this knowledge to leverage a successful career as a freelancer, as many professionals already do around the globe. But applying for work can be a different matter, and certs and degrees do ease the way in many cases, so let's discuss them.
Verified Courses
A verified course might be somewhere between $40–$200, depending on the course and the institution. Basically, you pay a premium to get your identity and assignments verified (this is what a verified certificate looks like.) You can find more about Coursera's Course Certificates and edX's Verified Certificates. You'll find they both have a huge offering of ML and data-science–related verified courses, as you can see on this edX search.
Notice that, whether you pay or not, the contents and materials of the course are exactly the same. What you get by paying is the certification that you actually took and passed the course.
Coursera Specializations
Coursera took the concept of verified courses a step forward by grouping some related courses and adding a capstone project to give you a specialization certificate.
Some specializations of interest to us are:
specialization courses institution Big Data 6 UC San Diego Deep Learning 5 deeplearning.ai Machine Learning 4 University of Washington Recommender Systems 5 University of Minnesota Introduction to Robotics 6 University of Pennsylvania Probabilistic Graphical Models (PGMs) 3 Stanford University
Coursera Master's Degree
Coursera's Master of Computer Science in Data Science (MCS-DS) is an actual, official master's degree issued by an accredited university. Topics in the program are heavily ML-related, and include:
data visualization
machine learning
data mining
cloud computing
statistics
information science
Course details:
Institution: University of Illinois at Urbana-Champaign
Price: $600 per credit-hour for a $19,200 in total tuition
Duration: 32 hours
edX XSeries and Professional Certificates
edX has an XSeries Program for courses within a single topic, in pretty much the same fashion as Coursera's Specializations. Such series of interest to us include:
series courses institution cost Microsoft Azure HDInsight Big Data Analyst 3 Microsoft $49–99 per course Genomics Data Analysis 3 Harvard University $132.30 Data Analysis for Life Sciences 4 Harvard University $221.40 Data Science and Engineering with Spark 3 UC Berkeley $49–99 per course
edX also has Professional Certificate Programs for "critical skills," including Data Science and Big Data, both offered by Microsoft.
edX MicroMasters and College Credit
You also have credit-eligible courses, which are not only verified, but may also serve you to claim for credit towards your B.S. or master's degree. There are, naturally, a lot of details in the fine print, so you'll have to do some extra research.
edX MicroMasters are precisely in this vein. Here are some interesting ones (costs are higher here, as you also pay hours of tuition towards a degree):
program courses institution cost Artificial Intelligence 4 Columbia University $1,200 Big Data 5 University of Adelaide $1,215 Data Science 4 UC San Diego $1,260 Robotics 4 University of Pennsylvania $1,256
Find out more to earn university credit on edX, and read the MOOCs for Credit report by Class Central.
Udacity's Nanodegrees
A nanodegree is something of degree, issued by Udacity. While Udacity isn't itself an accredited educational institution, they went to great lengths to partner with tech industry leaders to deliver the most market-targeted education possible --- in other words, to prepare you specifically with the skills that the labor market is demanding right now.
And we're really talking big names, here: Google, Amazon, IBM, Nvidia, Mercedes-Benz, DiDi, AT&T, among many others. And Udacity's partners not only co-design the study programs, but even have hiring agreements with Udacity!
Udacity and their partners even go as far as to publish estimated salary figures:
program time estimated salary Artificial Intelligence 6 months $59.4K to $250K Deep Learning TBD TBD Machine Learning 6 months $38.7K to $212K Robotics two 3-month terms $42k to $156k Self-Driving Car 9 months $67.8K to $265K
Get a job or your money back!
In fact, the ML nanodegree is part of the Nanodegree Plus program, which is probably one of the most reckless innovations in online learning: you study and graduate, and if you don't get a high paying job, Udacity refunds your tuition! Unbelievable.
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2017 STATE OF GLOBAL TECH SALARIES Insights into technology workers’ salaries and the hiring market OVERVIEW For the second year in a row, Hired has tapped into its data to reveal insights into technology workers’ salaries and the hiring market more generally. Because Hired facilitates the job searching process from the initial interview request all the way to the final job offer, we have unprecedented visibility into salaries across a variety of positions and companies. Most of the tools available to companies and job seekers are flawed and inaccurate. Salary calculators don’t account for company size, years of candidate experience or location, while many job sites are based on anonymous, self-reported data which can vary widely in accuracy. Hired’s data, on the other hand, is based on actual job offers made to real people. This second edition of our Second edition of Global State of Tech Salaries report is part of our larger effort to bring more transparency to the hiring process and provide an inside look at the compensation landscape for tech workers. As a result of our recent expansion into France, Australia and Singapore, we now have access to salary information in 16 of the world’s biggest tech markets, and have broadened this year’s report to reflect our truly global reach. Moreover, we recently began collecting voluntary demographic data from candidates on our platform, which allows us to analyze how race, age and bias can impact one’s salary. Ultimately, we want to empower candidates to understand their market value based on their skills and experience so that they can approach the job searching process armed with information. We also want to help companies recruit and hire with insight. We believe this transparency benefits everyone, so that individuals can find jobs they love and companies can attract the individuals who will drive their businesses forward. 1. A GLOBAL LOOK AT TECH SALARIES Globally, software engineers tend to draw significantly smaller salaries than their U.S.-based counterparts. While there are many factors that contribute to this, one of the most likely causes is that the United States’ tech market is the most mature, which ultimately leads to higher salaries. 2016 AVERAGE SOFTWARE ENGINEER SALARY BY MARKET Recent fluctuations with the euro and the pound mean that while candidates in these markets are seeing their salaries increase relative to the previous year, their purchasing power in the US has declined. YEAR-OVER-YEAR SALARY CHANGE FROM 2015 SF Bay Area | 3.28% Seattle | 2.14% Austin | 0.96% Chicago | 0.57% New York | 0.25% Boston | 0.24% LA | -0.13% London | -1.7% Denver | -2.63% Washtington D.C | -2.85% San Diego | -4.92% Toronto | -6.29% France | N/A Singapore | N/A Sydney | N/A Melcourne | N/A For decades, Silicon Valley has been the epicenter of the tech industry, but the rise of new technology and innovation hubs across the United States and the world are challenging the Bay Area’s reign. In fact, after adjusting for cost of living in San Francisco, cities like Austin, Melbourne, Seattle, and Toronto are increasingly attractive spots for tech workers to grow their careers. In Austin, the average salary for a software engineer on Hired is $110K. But this is the equivalent to making $198K in San Francisco when you consider the cost of living difference between the two cities. Notably, Austin-based companies are especially willing to relocate the right talent, with more than 60 percent of job offers going to candidates living outside the Lone Star State. In comparison, only 30 percent of offers from SF Bay Area companies are given to non-local candidates. Outside the U.S., we see a similar trend in Melbourne. Even though Melbourne’s average salary for software engineers is a relatively low $83K (A$107K), this is equivalent to making nearly $150K in San Francisco when factoring in cost of living. Like Austin, local companies are willing to relocate the right talent -- nearly a quarter of the candidates receiving offers from Melbourne-based companies are from outside of Australia. Our analysis shows it’s a great time for tech workers to consider a role outside Silicon Valley. Whether looking to stretch their salaries or to be a part of a growing tech hub, companies across the globe are ready and willing to do what it takes to bring great candidates to their markets. 2016 AVERAGE SOFTWARE ENGINEER SALARY ADJUSTED FOR COST OF LIVING IN SF San Francisco’s rising prices continue to make it an expensive option, even when compared to other historically pricey US cities. When you adjust for cost of living, the average software engineer salary in New York and Los Angeles have seen an 8% and 14% increase in their purchasing power relative to San Francisco over the last year. This year’s data reveals that higher salaries await candidates who are willing to move to a new city. In nearly every market, companies offer more money to individuals who are relocating than local candidates. This is particularly true of European, Canadian and Asian markets, where non-local candidates can earn up to 57 percent more than local candidates. Relocation becomes an even better option when you consider that most companies are willing to offer a package to help with moving expenses. 2016 TECH SALARY OFFERS FOR LOCAL VS. RELOCATION CANDIDATES 2. THE SATE OF SALARIES FOR PRODUCT MANAGERS AND DATA SCIENTIST The importance of an experienced software engineer is second to none, but as companies grow, product managers and data scientists become increasingly critical, a fact that’s underscored by our data. To understand how their salaries have changed, we analyzed year-over-year data for both roles in the US and the UK, our most mature international market. In the US, product managers bring in the highest average salary offers of any tech role at $138K, with strong year-over-year growth. While UK salaries are lower across the board, product managers are still coming out on top at $83K (£64K) on average in 2016. Data scientists in both countries are also seeing their salaries increase by a healthy margin as well. U.S. DATA SCIENCE AND PRODUCT MANAGEMENT SALARY GROWTH U.K. DATA SCIENCE AND PRODUCT MANAGEMENT SALARY GROWTH SKILLS FOR CANDIDATES RECEIVING THE HIGHEST INTERVIEW REQUESTS Product Management Business Development Project Management and Strategy Java Ruby Agile Methodologies Data Management Data Science Machine Learning Data Analysis Python SQL Statistics R 3. THE STATE OF BIAS At Hired, we believe it is important that companies and candidates understand the impact of bias, unconscious or not, on salaries and hiring practices. Recently we began collecting voluntary demographic data from candidates on our platform, allowing us to explore how a candidate’s identity affects the wages they receive and to share insight on the issues of employee diversity and hiring bias. AVERAGE PREFERRED SALARIES AND SALARY OFFERS BY RACE
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