#kafka online tutorial

[bigdatabootcamp]

Build Your Career with the Best Data Engineering Community Online

In today’s digital-first economy, data engineering is one of the most in-demand and rewarding tech careers. However, mastering this complex and evolving field isn’t just about self-study or online courses. Real growth often happens when you're part of a strong, supportive, and expert-driven community.

That’s exactly what the Big Data Bootcamp Data Engineering Community offers: a thriving ecosystem of professionals, mentors, and learners united by a common goal—to build and elevate careers in data engineering. Whether you’re just starting out or already working in tech, this online community offers the tools, guidance, and connections to help you succeed faster and more confidently.

Let’s explore why joining the right Data Engineering Community is a game-changer, and how Big Data Bootcamp’s platform stands out as the ultimate launchpad for your career in this exciting field.

Why Community Matters in Data Engineering

Learning to become a data engineer is more than following tutorials or earning certifications. The technology stack is wide and deep, involving concepts like distributed systems, data pipelines, cloud platforms, and real-time processing. Keeping up with these tools and practices is easier—and more effective—when you have a network of peers and experts to support you.

A professional community helps by providing:

1. Mentorship and Guidance

Tap into the knowledge of experienced professionals who have walked the path you’re on. Whether you're facing technical challenges or career decisions, mentors can provide direction that accelerates your progress.

2. Collaborative Learning

Communities foster an environment where learning is not just individual but shared. Group projects, open-source contributions, and peer reviews are common in active communities, offering real-world skills you can't gain in isolation.

3. Industry Insights

Staying current in data engineering requires awareness of trends, best practices, and innovations. A connected community can be your real-time feed for what’s happening in the world of big data.

4. Career Opportunities

Networking is one of the fastest ways to land a job in tech. Many community members share job leads, referrals, and insider info that isn't publicly posted.

5. Accountability and Motivation

When you're surrounded by motivated people with similar goals, it keeps you inspired and on track. Sharing progress and celebrating milestones fuels ongoing commitment.

Introducing the Big Data Bootcamp Community

The Big Data Bootcamp Data Engineering Community is more than just a chat group or online forum. It’s an organized, high-impact environment designed to provide real value at every stage of your career journey.

Hosted at BigDataBootcamp.com, the platform combines the best of structured learning, peer support, and professional development. It’s tailored specifically for:

Aspiring data engineers

Bootcamp and college graduates

Career switchers from software development, analytics, or IT

Experienced data professionals looking to level up

Here’s what makes this online community stand out.

What You Get as a Member

1. Access to Expert Mentors

Learn from top-tier professionals who have worked with companies like Google, Amazon, Meta, and cutting-edge startups. These mentors actively guide members through code reviews, project feedback, and one-on-one career advice.

2. Structured Learning Paths

Community members can access exclusive workshops, tutorials, and study groups aligned with in-demand skills like:

Data pipeline design

Apache Spark, Kafka, and Airflow

Cloud data platforms (AWS, GCP, Azure)

Data warehouse tools like Snowflake and BigQuery

Advanced SQL and Python scripting

3. Real-World Projects

Apply your skills in collaborative projects that simulate actual industry challenges. This builds not just your knowledge, but also your portfolio—essential for standing out to employers.

4. Career Acceleration Services

Take advantage of:

Resume and LinkedIn profile reviews

Job interview prep sessions

Access to a private job board

Referrals from alumni and hiring partners

5. Regular Events and Networking

Participate in:

Webinars with industry leaders

AMAs with senior data engineers

Virtual meetups and hackathons

Fireside chats and alumni Q&As

These events keep the community lively and ensure you stay connected with the pulse of the industry.

6. Supportive Peer Network

Exchange ideas, ask questions, and get feedback in a welcoming environment. Whether you’re debugging a pipeline or seeking advice on cloud certification, the community is always there to help.

Proven Success Stories

Here are just a few examples of how the community has changed lives:

Manoj, a mechanical engineer by training, transitioned into a data engineering role at a healthcare company within six months of joining the community.

Ayesha, a computer science graduate, used the community's project-based learning approach to build a portfolio that landed her a job at a fintech startup.

Carlos, an IT administrator, leaned on mentorship and mock interviews to land a role as a data engineer with an international consulting firm.

These success stories aren't exceptions—they're examples of what's possible when you're part of the right support system.

Why Choose Big Data Bootcamp Over Other Communities?

While other online tech communities exist, few offer the blend of quality, focus, and career alignment found at Big Data Bootcamp. Here’s why it stands out:

Focused on Data Engineering – It’s not a generic tech group. It’s built specifically for those in data engineering.

Built by Practitioners – Content and mentorship come from people doing the work, not just teaching it.

Job-Oriented – Everything is aligned with real job requirements and employer expectations.

Inclusive and Supportive – Whether you're just beginning or well into your career, there's a place for you.

Live Interaction – From live workshops to mentor check-ins, it's a dynamic experience, not a passive one.

How to Join

Becoming part of the Big Data Bootcamp Community is simple:

Visit BigDataBootcamp.com

Explore bootcamp offerings and apply for membership

Choose your learning path and start attending community events

Introduce yourself and start engaging

Membership includes lifetime access to the community, learning content, events, and ongoing support.

Final Thoughts

If you're serious about becoming a high-performing data engineer, you need more than just courses or textbooks. You need real connections, honest guidance, and a community that pushes you to grow.

At Big Data Bootcamp, the online data engineering community is built to do just that. It’s where careers are born, skills are refined, and goals are achieved.

Join us today and start building your future with the best data engineering community on the internet.

The tech world moves fast. Move faster with the right people by your side.

[tech-insides]

How Can Beginners Start Their Data Engineering Interview Prep Effectively?

Embarking on the journey to become a data engineer can be both exciting and daunting, especially when it comes to preparing for interviews. As a beginner, knowing where to start can make a significant difference in your success. Here’s a comprehensive guide on how to kickstart your data engineering interview prep effectively.

1. Understand the Role and Responsibilities

Before diving into preparation, it’s crucial to understand what the role of a data engineer entails. Research the typical responsibilities, required skills, and common tools used in the industry. This foundational knowledge will guide your preparation and help you focus on relevant areas.

2. Build a Strong Foundation in Key Concepts

To excel in data engineering interviews, you need a solid grasp of key concepts. Focus on the following areas:

Programming: Proficiency in languages such as Python, Java, or Scala is essential.

SQL: Strong SQL skills are crucial for data manipulation and querying.

Data Structures and Algorithms: Understanding these fundamentals will help in solving complex problems.

Databases: Learn about relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).

ETL Processes: Understand Extract, Transform, Load processes and tools like Apache NiFi, Talend, or Informatica.

3. Utilize Quality Study Resources

Leverage high-quality study materials to streamline your preparation. Books, online courses, and tutorials are excellent resources. Additionally, consider enrolling in specialized programs like the Data Engineering Interview Prep Course offered by Interview Kickstart. These courses provide structured learning paths and cover essential topics comprehensively.

4. Practice with Real-World Problems

Hands-on practice is vital for mastering data engineering concepts. Work on real-world projects and problems to gain practical experience. Websites like LeetCode, HackerRank, and GitHub offer numerous challenges and projects to work on. This practice will also help you build a portfolio that can impress potential employers.

5. Master Data Engineering Tools

Familiarize yourself with the tools commonly used in data engineering roles:

Big Data Technologies: Learn about Hadoop, Spark, and Kafka.

Cloud Platforms: Gain experience with cloud services like AWS, Google Cloud, or Azure.

Data Warehousing: Understand how to use tools like Amazon Redshift, Google BigQuery, or Snowflake.

6. Join a Study Group or Community

Joining a study group or community can provide motivation, support, and valuable insights. Participate in forums, attend meetups, and engage with others preparing for data engineering interviews. This network can offer guidance, share resources, and help you stay accountable.

7. Prepare for Behavioral and Technical Interviews

In addition to technical skills, you’ll need to prepare for behavioral interviews. Practice answering common behavioral questions and learn how to articulate your experiences and problem-solving approach effectively. Mock interviews can be particularly beneficial in building confidence and improving your interview performance.

8. Stay Updated with Industry Trends

The field of data engineering is constantly evolving. Stay updated with the latest industry trends, tools, and best practices by following relevant blogs, subscribing to newsletters, and attending webinars. This knowledge will not only help you during interviews but also in your overall career growth.

9. Seek Feedback and Iterate

Regularly seek feedback on your preparation progress. Use mock interviews, peer reviews, and mentor guidance to identify areas for improvement. Continuously iterate on your preparation strategy based on the feedback received.

Conclusion

Starting your data engineering interview prep as a beginner may seem overwhelming, but with a structured approach, it’s entirely achievable. Focus on building a strong foundation, utilizing quality resources, practicing hands-on, and staying engaged with the community. By following these steps, you’ll be well on your way to acing your data engineering interviews and securing your dream job.

[rudrasonline]

Mastering Big Data: A Comprehensive Guide to Online Learning - rudrasonline

Learning Big Data Courses Online– RudraOnline can be a rewarding endeavor, and there are numerous resources available. Here's a step-by-step guide to help you get started:

Understand the Basics:

Familiarize yourself with the basic concepts of big data, such as volume, velocity, variety, veracity, and value (the 5 V's).

Learn about distributed computing and parallel processing.

Programming Languages:

Gain proficiency in programming languages commonly used in big data processing, such as Python, Java, or Scala.

Foundational Technologies:

Learn the fundamentals of big data technologies like Apache Hadoop and Apache Spark. These technologies are widely used for distributed storage and processing.

Online Courses:

Explore online learning platforms that offer big data courses. Platforms like Coursera, edX, Udacity, and LinkedIn Learning provide courses from universities and industry experts.

Certifications:

Consider pursuing certifications in big data technologies. Certifications from vendors like Cloudera or Hortonworks can enhance your credibility.

Hands-on Practice:

Practice what you learn by working on real-world projects. Platforms like Kaggle provide datasets for hands-on experience.

Documentation and Tutorials:

Read official documentation and follow tutorials for big data technologies. This will help deepen your understanding and troubleshoot issues.

Books:

Refer to books on big data, such as "Hadoop: The Definitive Guide" by Tom White or "Spark: The Definitive Guide" by Bill Chambers and Matei Zaharia.

Community Involvement:

Join online forums and communities where big data professionals share knowledge and experiences. Participate in discussions and ask questions when needed.

Specialize:

Depending on your interests and career goals, consider specializing in specific areas within big data, such as data engineering, data science, or machine learning.

Advanced Topics:

Explore advanced topics like Apache Kafka for real-time data streaming or Apache Flink for stream processing.

Networking:

Attend webinars, conferences, and meetups related to big data. Networking with professionals in the field can provide valuable insights and potential job opportunities.

[gkindex-blog]

Learn Java Online at Your Own speed with GKIndex; free interactive Java & Apache Kafka tutorial for Beginners who want to learn Java fast today & become an Expert in Days.

[mercurypyrite]

spoilers for trailblazer-related plot points during the jarilo-vi final boss fight, though not for the boss themself

ok so theory time

we met qlipoth the preservation in the simulated universe first (in world 1) & then later unlocked the path of preservation

(we also got the fire element in jarilo-vi, an ice world, which is a related-but-separate thing. this is kinda a stretch but i think it’d be interesting to get an element that counters wind like fire does ice. definitely not for angst reasons, i promise. and i think it’s cute that we got to match paths with march 7th and potentially dan heng first)

since we met lan the hunt next (in world 2), if the trend continues we’ll get hunt mc next

…i don’t actually know which aeon we meet in world 3, if any — i haven’t gotten that far and wasn’t able to find much online 😓 input is welcome [edit] in world 3 we meet nanook the destruction and immediately get murked (thank you @yeeted-into-the-multiverse!) why am i not surprised… at least we got an interaction with them, i guess, even if that interaction was murder

but from what my friends have told me and what i’ve dug up online, it seems like we meet ix the nihility in world 4 and yaoshi the abundance in world 5. correct me if i’m wrong bc, again, i haven’t gotten that far myself

(and of course we may meet other aeons like fuli the remembrance and aha the elation in world 1, it’s just that they don’t have playable paths.)

so i’m gonna guess that, for path progression, it’ll go like:

destruction [canon]

preservation [canon]

hunt

???

nihility

abundance

???

not sure whether we’d get erudition (nous) or harmony (xipe) first but i kinda wanna go with harmony…? which would leave my beloved aoe trailblazer ‘til last rip

^and this is mostly because we got asta as a kind of “tutorial” character — and i know we were given herta too! asta just came first.

(but also i think it’d be funny to see trailblazer bounce from harmony to nihility. imagine the whiplash for their teammates.)

just for kicks, elements to go along with them:

physical [canon]

fire [canon]

ice

wind

lightning

imaginary

quantum

reasoning:

canon.

canon.

wind is fast & i think ice is a good counter to that. slow enemies down, freeze them. can’t attack if you’re frozen.

this was actually the last one i put down via process of elimination kek. but, coincidentally, it ties back into matching with march (ice) and dan heng (wind) again so i’m happy with it.

honestly i think it’d be really neat if the trailblazer ended up with a similar skillset to kafka — lightning + nihility.

imaginary and quantum both feel like endgame elements to me since they kinda stick out against the more “mundane” elements.

a lot of early-game enemies in the space station are weak to quantum. said enemies are the antimatter legion, followers of nanook, the big bad. so it wouldn’t surprise me if they became late-game enemies as well, or if nanook shared that weakness.

i think that’s everything i’ve got. i’ll reblog this with updates as i’m proven wrong or right.

i’m probably not the first person to bring this whole thing up but i don’t care because i had fun thinking about it /lh

[kismetnama]

90 days to go | 100 DOP

Was I productive? Yes.

Did my productivity directly or indirectly relate to mu thesis work? I decline to answer.

In the last few days I managed to read metamorphosis my Franz Kafka, crochet granny squares for a scarf, tried some new recipes, binge watched crochet tutorials and Jack Edward's YouTube videos.

My thesis work you ask? I did find new readings for my literature review, have interviews coming up (my thesis is an Auto-ethnographic, qualitative research based) and attended my online classes.

Also instead of using the term 'day 10 update' I have decided to use the '90 days to go' approach for 100 dop. It makes me feel as if I am on a mission.

[generatour1]

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[automationqa]

20+ Resources for Test Automation Engineers

Test automation is an essential part of the software development lifecycle. It helps teams to deliver high-quality software at a faster pace by automating repetitive tasks and reducing the time and effort needed for manual testing.

However, test automation is a constantly evolving field, and staying up-to-date with the latest tools, technologies, and best practices can be a challenge. To help test automation engineers stay on top of their game, here are 20+ resources that can be valuable for their professional development: 

Selenium - An open-source tool for web application testing that supports multiple programming languages. 

Appium - An open-source mobile automation testing tool. 

TestNG - A testing framework for the Java programming language. 

JUnit - A testing framework for the Java programming language. 

Cucumber - A tool for behavior-driven development (BDD) that supports multiple programming languages. 

PyTest - A testing framework for the Python programming language. 

Robot Framework - A generic test automation framework that supports multiple programming languages. 

TestComplete - A commercial tool for desktop, mobile, and web application testing. 

SoapUI - An open-source tool for testing web services and APIs. 

Postman - A commercial tool for testing web services and APIs. 

JMeter - An open-source tool for load and performance testing. 

Gatling - An open-source tool for load and performance testing. 

Apache Kafka - A distributed streaming platform used for building real-time data pipelines and streaming applications. 

Apache Storm - A distributed real-time computation system used for processing large streams of data. 

Apache Flink - An open-source framework for distributed stream and batch data processing. 

Apache Spark - An open-source big data processing framework that supports batch processing, streaming, machine learning, and graph processing. 

Machine Learning Mastery - A website that provides tutorials, courses, and resources for machine learning and artificial intelligence. 

TensorFlow - An open-source software library for dataflow and differentiable programming used for machine learning and artificial intelligence. 

Keras - An open-source software library for deep learning that runs on top of TensorFlow. 

The Testing Planet - A magazine dedicated to software testing that provides articles, tutorials, and industry news. 

Ministry of Testing - A community-driven website that provides resources, training, and events for software testing professionals. 

Software Testing Help - A website that provides tutorials, articles, and tools for software testing and quality assurance. 

LinkedIn Learning - An online learning platform that provides courses on software testing, test automation, and other related topics. 

In conclusion, test automation is a complex and constantly evolving field, and staying up-to-date with the latest tools, technologies, and best practices is crucial for success. The resources listed above can provide valuable support and guidance for test automation engineers at every stage of their professional development. 

[mainsmr]

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SET OPENING PAGE IN JUTOH TRIAL

SET OPENING PAGE IN JUTOH TRIAL

I'm going to use Kafka's The Trial for this tutorial. That's because your book file needs to be pretty simple to convert it to ebook. If your book is in an MS Word file, you should actually have saved a simple copy, before you did any print formatting. In either case, skip down to the lower sections.*** *** If you used Scrivener or Adobe InDesign you can export as an Epub file directly if you used another open source word processor you can probably save as RTF or HTML. And that may seem depressing, but it should be liberating: you don't need to spend a lot of time or energy making your ebooks perfect, just make sure they work and are clean, and people can read your book without distraction. If you're like me, you're probably thinking these don't look very good. I'm taking a picture of a bunch of the books on my Kindle so you can get a sense of what they look like. And maybe you'll offset the first line in all caps, or a slightly bolded or larger first sentence. The first paragraphs of each chapter will be non-indented. What you can doīasically, you'll use "H1" or "H2" tags for headers. So don't get hung up on the small details. Even if you try to use a dropcap or special formatting, it might look funny. The most important thing is that - even if it doesn't look the same - it doesn't look "broken" or obviously flawed.įor this reason, most mainstream publishers use extremely simple ebooks with no decoration at all. It's very hard to get your file to look exactly the same everywhere.

SET OPENING PAGE IN JUTOH CODE

While this can be done, my complex code would look fine on Kindle or Barnes & Noble but might like strange on Kobo. I was trying to approach it like a print book, and insert images and special designs, and fixed fonts. When I first started learning ebook formatting, it was frustrating. While you don't really need to learn this code, it will help if you need to fine tune the details. To achieve this, ebook formats use something very similar to html code. This is so people using various ereaders can set their own options, change the fonts and text size, to make the reading experience suit their preferences. Unlike print books, for which you want everything to be "fixed" and perfect, ebooks need to "flow." Most ebook stores use a file format called "epub" - but Amazon/Kindle uses a slightly modified file format called "mobi." Most bookstore chains have their own ereader device and their own bookstore but some companies like Smashwords, BookBaby, and Lulu offer "distribution" - which means they'll send your ebook out to all the online retailers and keep track of sales for you. "Ebooks" are digital versions of your book that can be read on tablets and smartphones. Luckily, you can do it for free, and it can be pretty easy - if you aren't picky about the little details (and I'll explain why you shouldn't be).īelow you'll find a few different methods for converting your document to epub and mobi formats, as well as formatting a Smashwords file (ideal for broader distribution). So even while you're formatting for print, you should be thinking about ebook conversion. Since ebooks have no production costs, they let you be much more flexible in pricing, and can be a powerful marketing tool to attract new readers. No matter what kind of book you're publishing, ebook sales will probably be your biggest numbers. I'm not sure what to do with them yet but you can check them out here: Ebook Conversion and Formatting Tools. Recently I had a couple custom ebook formatting and conversion tools built. Until then, you can read through the guide down below or watch the videos above. But I'll start adding individual videos here for each separate method of making an ebook (From InDesign, through Scrivener or Jutoh, etc) I plan to have about 25 of them. That's the simplest process, which I recommend for beginners.

SET OPENING PAGE IN JUTOH HOW TO

The video below will show you how to convert from Word (.docx) to epub and mobi formats with my free ebook conversion tool.Īnd this video will teach you how to edit your epub file with Sigil Above is a video explaining the basics of ebook publishing, formatting and conversion.

[360digitmg-bangalore]

Data Science Resource Hub

I began with Python and tried a few books and then I got here back to R as a outcome of ggplot appeared higher than matplotlib. Learn to ask the best questions, manipulate information sets, and create visualizations to communicate outcomes. An open-source framework, Hadoop is used for distributed processing and distributed storage of enormous knowledge units. Candidates will need to strategy challenges at a better stage, employing the proper strategy to make the maximum use of time and human sources. This two-day course empowers you to transcend “spotting trends” and make data-driven enterprise forecasts. Does your audience often leave with out understanding the important thing points from your analysis? Come to this courses to learn how to create compelling data visualisations that inform and drive motion. Gain expertise with Python to take your information analyst recreation to the following degree. In this month, you will learn alternative ways to deploy your fashions. And if you put forward your greatest efforts and follow this learning path – you’d be in a fantastic place to start cracking information science interviews by the top of 2020. And should you put ahead your finest efforts and comply with this studying path – you’d be in a great position to start cracking knowledge science interviews by the end of 2021. Follow together with at some point within the lifetime of actual knowledge scientists engaged on real tasks. Get on-the-job insights to assist put together you to deal with the next problem or select your next data science position. Build information science expertise, be taught Python & SQL, analyze & visualize information, build machine studying models. SAS Tutorial Machine Learning Fundamentals Ari Zitin explores determination tree and neural network models, then exhibits examples of machine learning duties. This webinar sequence is designed for individuals serious about enhancing their data science skills utilizing SAS® or looking to enter the sphere of information science. We’ll train you tips on how to leverage Docker to ease your deployments and navigate code written by data scientists . You will be taught to make use of Apache Airflow, Apache Spark, and Kafka like a forklift to maneuver data round. Working with Time Series Data – Organizations all over the world rely heavily on time-series data and machine learning has made the scenario much more exciting.best institute for best institute for data science in hyderabad Our skilled trainers will lead you along this journey, taking you from scratch to knowledgeable level. Processing knowledge effectively may be difficult because it scales up. Building up from the expertise we built at the largest Apache Spark users on the planet, we provide you with an in-depth overview of the do’s and don’ts of one of the most popular analytics engines on the market. SAS Tutorial Online SAS Training Course Resources Anna Rakers introduces you to SAS training course assets that will help you learn SAS and obtain your targets. Browse videos, articles and different studying materials to supplement the SAS® Academy for Data Science. The training gave me a lot of grip and insights on the subject. How to make use of pandas, cleansing up your data, and plotting data have been probably the most interesting components for me. Understand the trade-offs essential to bring a mannequin into manufacturing, together with the info, scoring, modeling, training, and monitoring. This downside went away when I obtained a take-home assignment from a company who approached me for R related work. After using each R and Python for take-home project work, I never wanted to the touch R once more. It is type of the identical as when you are doing software program growth. There is one other aspect to this.Business Problems. The model you construct, the comparisons you did, and the accuracy you achieved, how it is benefiting the business? You see, a data scientist’s job has no meaning if he can’t bring some profit or benefit or some value addition to the enterprise. Contributing to the staff is the place my social and my communication abilities ended. I assume every of us have to personalize our journeys. Our setting, our expertise, our expertise, our attitude, our work ethic, our backgrounds, and our learning capacities, all are totally different and unique. That is why perhaps tracing somebody else’s path by no means works. Explore top-quality degrees you could full at your pace from a world-class college. Many degrees have courses or Specializations you can begin today. SAS analytics options transform information into intelligence, inspiring clients around the globe to make bold new discoveries that drive progress. The SAS Academy for Data Science offers a quantity of packages to help build your analytics profession. A collection of interviews with high data scientists, who talk about problem fixing, artistic approaches to knowledge, tenacity and the shocking importance of relationships. Blog Post A Data Scientist Finds Her Way in a World of Data Melissa Torgbi explains how she grew to become a data scientist, and provides tips for anybody who desires to observe an analogous path. This webinar series is designed for individuals who want to showcase their information science expertise utilizing the most recent instruments to garner perception from data. I appreciated every aspect of the training and want to thank the trainers. Find the right programs to develop your team’s Data & AI expertise, or design learning journeys at scale to empower your whole organization. This GoDataDriven coaching offers a 3-day deep-dive into Apache Spark. Learn to grasp the tools Apache Spark offers, unlock its potential and advance your Data Science skills. In this month, you'll learn to work with Time Series information and different techniques to resolve time sequence associated issues. Extended Storytelling Skills – Storytelling is extra of an art than a talent. By explaining knowledge science, machine learning ideas to my associates and different individuals. But because my freelance work and knowledge science studying require me to spend so much of time in entrance of my computer, I don’t get the chance to train this methodology much. One way to crack this is by looking at reality. If you realize any real-life information scientists, knowledge analysts, and machine studying engineers , it will be a fantastic thought to speak to them about their work. If you don’t know anyone then you can always check blogs and articles. We have introduced a Masters's program in Data Science that will provide you with the information and the instruments to accelerate your profession. You know Machine Learning, but working with it every day is a unique story. This course is full of finest practices, fashions, code, algorithms and a framework to improve your tasks. Learning paths are simply one of the in style and in-demand resources we curate at the start of the brand new yr. We’ve received a ton of queries lately asking when we could be releasing the training paths for 2020.

For more information

360DigiTMG - Data Analytics, Data Science Course Training Hyderabad

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[gkindex-blog]

All You Need to Know About The Advantages of Java

Java can be found anyplace you look at. It's an essential language for Android improvement. You will discover it in web applications, government sites, and big data technologies, for example, Hadoop and Apache Storm. What's more, it's additionally a classic decision for logical projects, particularly natural language processing.

Java was dominating mobile even in pre-cell phone days – the first mobile games in the mid-2000s were for the most part made in Java. You can learn free Java online tutorials and practice it properly to know more about it. Java is the only language that every developer needs to know about it properly for doing the programming.

Here are discussed some of the advantages of Java. Explore it properly.

1.            Object-oriented programming

Java grasps object-oriented programming (OOP) – a coding idea where you do not just characterize the sort of data and its structure, yet in addition, the arrangement of functions applied to it. Thusly, your data structure turns into an object that would now be able to be controlled to make connections between various objects.

Rather than another methodology – procedural programming – where you need to adhere to an arrangement of guidelines utilizing variables and functions, OOP permits you to aggregate these variables and functions by setting hence marking them and alluding to functions with regards to every particular object.

2.            The standard for enterprise computing

Enterprise applications are Java's most prominent resource. It began, back in the 90s when associations started searching for strong programming tools that weren't C. Java supports plenty of libraries – building blocks of any enterprise system – that assist engineers with making any function an organization may require. The huge talent pool additionally helps – Java is the language utilized for introduction to PC programming in many schools and colleges. In addition, its integration abilities are noteworthy as the vast majority of the facilitating suppliers support Java. To wrap things up, Java is similarly modest to keep up since you don't need to rely upon explicit hardware infrastructure and can run your servers on a machine you may have.

3.            Shortage of security risks

You may experience the idea by using free Java online tutorials that Java is a protected language however that is not so much obvious. The language itself doesn't shield you from vulnerabilities, yet a portion of its highlights can spare you from normal security flaws. To begin with, contrasted with C, Java doesn't have pointers. A pointer is an object that stores the memory address of another value that can make unauthorized access to memory. Second, it has a Security Manager, a security strategy made for every application where you can indicate get to rules. This permits you to run Java applications in a "sandbox," reducing risks of harm.

These are the significant advantages of using Java mentioned above. Learn to use it properly to get the best result.

GKIndex offers to learn kafka & Java for free and helps you to integrate into the perfect position. If you need any assistance regarding any issue, you can contact us anytime.

[ahbusinesstechnology]

The best free ebooks resources

What are free ebooks resources?

These resources will provide you a huge online-ebooks. Furthermore, they are completely free! In addition, these resources contain many topics from business to technology ...so on. Besides, some of them are support view on mobile mode and easy to get pdf file.

Where are they store?

You can find these resources below which their full description. Hence, they are very useful for doing research and study and of course they are free for all access, so you can download as many as you want. We list out these to many different categories below for easy to find. Libraries Gutenberg: Project Gutenberg was the first to supply free ebooks, and today they have almost 30,000 free titles in stock. Free-eBooks.net: Besides browsing topics such as biography, fan fiction, games, history, or tutorials, you can submit your own ebook, too. ManyBooks.net: You can conduct an advanced search, type in a title or author, browse categories or select books by language, from Finnish to Bulgarian to Catalan to Swedish. DailyLit: Get free downloads sent to your email by RSS feed. iBiblio: Find archives, ebooks, tutorials, language books, and more from iBiblio. Authorama: This public domain book site has a wide variety of ebooks for free, by Lewis Carroll, Emerson, Kafka, and more. Bartleby: While Bartleby charges for some titles, it has a free ebook store here. bibliomania: You will find over 2,000 classic texts from bibliomania, plus study guides, reference material and more. Baen Free Library: You can download ebooks for HTML, RTF, Microsoft Reader and for Palm, Psion, and Window CE. eReader.com: eReader.com has many classic lit selections for free. Read Print Library: These novels and poems are all free. ebook Directory: From children's books to IT books to literature to reference, you'll find lots of free titles and book packages here. Planet PDF: Planet PDF has made available classic titles like Anna Karenina and Frankenstein for free. Get Free Ebooks: This website has free ebooks in categories from writing to environment to fiction to business, plus features and reviews. Globusz: There are no limits on the number of free books you can download on this online publishing site. eBookLobby: You'll find lost of self-help, hobby and reference books here, plus children's fiction and more. Bookyards: This online "library to the world" has over 17,000 ebooks, plus links to other digital libraries. The Online Books Page: You'll be able to access over 35,000 free ebooks from this site, powered by the University of Pennsylvania. Starry.com: These novels and anthologies were last updated in 2006, but you'll still find an interesting selection of online and virtual novels. eBook Readers Getting reviews and product information for all kinds of ebook readers, including the Kindle, you will have a full reviews before making decisions to purchase something. E-book Reader Matrix: This wiki makes it easy to compare ebook reader sizes, battery life, supported formats, and other qualifications. Amazon Kindle: Learn about, shop, and discover titles for the Kindle here. Abacci eBooks: All the books here are for Microsoft Reader. eBook Reader Review: TopTenReviews lists reader reviews from 2009. List of e-book readers: Learn about all of the different ebook readers from Wikipedia. E-book readers at a glance: This guide reviews and compares the new, cool readers. Free iPhone ebook readers head-to-head: Reality Distortion ranks iPhone ebook readers. About eBooks These links will connect you to ebook news, new title releases, and e-reader information. In addition, these resources support mobile views. TeleRead: This blog shares news stories about ebooks and digital libraries. MobileRead Forums: Learn about new ebook releases, clubs, and readers. E-book News: Technology Today has made room for a whole section on ebook news. Ebook2u.com: Get the latest headlines about readers, troubleshooting, titles, and more. The eBook coach: Learn how to write a successful ebook. Audio and Mobile Getting ebooks on your iPhone, iPod, BlackBerry, Palm, or other mobile device, you have many options to expand your knowledge on mobile devices. Feedbooks: You can download books for any mobile device here. Books in My Phone: Read ebooks on a java-enabled phone when you download them here. You can also manage a reading list. Barnes & Noble eBooks: Get NYT titles, new releases and more for your iPhone, BlackBerry, or computer. MemoWare: Get literature, poetry, and reference books for your PDA. Audible.com: Here you can download books to your iPod or mp3 player. iTunes: iTunes has audiobooks for iPhones and iPods. LibriVox: Get free audio book files on this site, or volunteer to record your narration for other books. eReader.comMobile: Get the mobile-friendly version of eReader.com here. Business and Education Turning to these ebook lists and resources for help with classes and your career is so very important for your personal future plan. Moreover, they are huge and well-organisation. Open Book Project: Students and teachers will find quality free textbooks and materials here. Digital Book Index: This site has over 140,000 titles, including textbooks and a pending American Studies collection. Classical Authors Directory: Get lesson plans, audio files, ebooks, and more from authors like Washington Irving, Benjamin Franklin and Homer. The Literature Network: Find classics, from Balzac to Austen to Shakespeare, plus educational resources to go along with the plays, short stories, and novels. OnlineFreeEbooks.net: All kinds of business, hobby, education textbooks, and self-teaching books are available for free on this site. Free Ebooks and Software: Learn how to do your own taxes and more from the books here. eLibrary Business Ebooks: Get emarketing, how-to, and other business ebooks here. Free Business eBooks: This guide has links to all kinds of free business ebooks. Data-Sheet: Data-Sheet finds ebook pdfs. Pdfgeni.com: Type into the search box the type of book you want to read, such as business education or vampire fiction. Ebook Search Engine: Simply type in your search and choose to have results displayed as PDFs or Word documents. Ebook Engine: This engine brings up free ebooks. eBook Search Queen: You can search ebooks by country here. ebookse.com: Browse by category or type your search into the box to bring up your query. Addebook: Free Ebook Search Engine: This tool is Google's ebook search engine. Boocu: Boocu can pull up thousands of ebooks and digital resources. Twitter Keeping up with ebook news, new titles, e-readers, and more by following these Twitter feeds is very well. The social channel is so very important to improve your knowledge. @AnEbookReader: Get tech reviews, accessories news, and more for ereaders and ebooks. LibreDigital: This company helps people find what they want to read and watch, on any medium. @e_reading: This feed comments on Kindle news and more. @RogerSPress: Roger publishes ebooks and has been reading them for 10 years already. @DigiBookWorld: Read about the latest trends in digital publishing. @ebooksstore: Follow @ebooksstore for interesting ebook news and releases. @ebookvine: This feed is all about Kindle. @vooktv: Now you can watch books on high-quality video online. @ebooklibrary: This is a feed for anyone who wants to learn more about free ebooks. @ericrumsey: Eric is a librarian who loves ebooks, his iPhone, and the Internet. @namenick: Nick Name is an ebook addict and mobile fiction writer. @KindleZen: Get the latest in Kindle news and hacks. Tech eBooks Get programming, design, and other tech assistance when you head to these ebook resources. FreeComputerBooks.com: Find magazines and IT books for reference and general interest. OnlineComputerBooks.com: Find free computer ebooks on networking, MySQL, Python, PHP, C++, and more. KnowFree.net: KnowFree has mostly tech books for download, plus some business titles. FreeTechBooks.com: This site has downloads in categories such as artificial intelligence, functional programming, and parallel computing. Tech Books for Free: From the web to computer programming to science, you'll find all sorts of tech ebooks here. Poetry Find poetry ebooks and collections here. everypoet.com: Read classic poetry on this site. PoemHunter.com: Download poems in PDF format here. Poetry: You'll find poetry ebooks for download on this site. Kids Share these interactive ebook resources with young readers. International Children's Digital Library: The ICDL is a colorful site devoted to children's ebooks. ebook88: On this site, there's a Christmas Bookshelf, and plenty of other kids' ebook links. Children's Storybooks Online: Find kids' storybooks, home schooling materials, and more. Tumble Books: This Tumble BookLibrary features fun, animated, talking picture books. Raz-Kids.com: This is another interactive kids' book site that helps kids learn to read. Children's Books Online: the Rosetta Project, Inc.: Here you'll find loads of books and translations for kids. Read.gov: From children's classics to in-progress digital books, Read.gov has excellent ebook resources. Storyline Online: The Screen Actors Guild Foundation presents Storyline Online with streaming videos of actors reading children's books. Miscellaneous From social networking and ebooks to bundles of books, turn here. Scribd: This ebook finder and social network shares what people are currently reading, and lets you upload your own book. Diesel: Diesel has 500,000 ebook store downloads, including custom bundles, mobile downloads, and some free titles. eBooks.com: Get NYT bestsellers for $9.99 each, plus all kinds of academic ebooks, non-fiction, and more.  

Final Word

Phew, they are a lot and free. Therefore, they are important and necessary. You can read carefully and find exactly what you want. On the other hand, I will add more content for this topic later, so you can check the updated posts. I hope you enjoy this post and find something is useful for you. Read the full article

[udemy-gift-coupon-blog]

CCA 131 - Cloudera Certified Hadoop and Spark Administrator ##FreeCourse ##UdemyFrancais #Administrator #CCA #CERTIFIED #Cloudera #Hadoop #Spark CCA 131 - Cloudera Certified Hadoop and Spark Administrator CCA 131 is certification exam conducted by the leading Big Data Vendor, Cloudera. This online proctored exam is scenario based which means it is very hands on. You will be provided with multi-node cluster and need to take care of given tasks. To prepare the certification one need to have hands on exposure in building and managing the clusters. However, with limited infrastructure it is difficult to practice in a laptop. We understand that problem and built the course using Google Cloud Platform where you can get credit up to $300 till offer last and use it to get hands on exposure in building and managing Big Data Clusters using CDH. Required Skills Install - Demonstrate an understanding of the installation process for Cloudera Manager, CDH, and the ecosystem projects. Set up a local CDH repository Perform OS-level configuration for Hadoop installation Install Cloudera Manager server and agents Install CDH using Cloudera Manager Add a new node to an existing cluster Add a service using Cloudera Manager Configure - Perform basic and advanced configuration needed to effectively administer a Hadoop cluster Configure a service using Cloudera Manager Create an HDFS user's home directory Configure NameNode HA Configure ResourceManager HA Configure proxy for Hiveserver2/Impala Manage - Maintain and modify the cluster to support day-to-day operations in the enterprise Rebalance the cluster Set up alerting for excessive disk fill Define and install a rack topology script Install new type of I/O compression library in cluster Revise YARN resource assignment based on user feedback Commission/decommission a node Secure - Enable relevant services and configure the cluster to meet goals defined by security policy; demonstrate knowledge of basic security practices Configure HDFS ACLs Install and configure Sentry Configure Hue user authorization and authentication Enable/configure log and query redaction Create encrypted zones in HDFS Test - Benchmark the cluster operational metrics, test system configuration for operation and efficiency Execute file system commands via HTTPFS Efficiently copy data within a cluster/between clusters Create/restore a snapshot of an HDFS directory Get/set ACLs for a file or directory structure Benchmark the cluster (I/O, CPU, network) Troubleshoot - Demonstrate ability to find the root cause of a problem, optimize inefficient execution, and resolve resource contention scenarios Resolve errors/warnings in Cloudera Manager Resolve performance problems/errors in cluster operation Determine reason for application failure Configure the Fair Scheduler to resolve application delays Our Approach You will start with creating Cloudera QuickStart VM (in case you have laptop with 16 GB RAM with Quad Core). This will facilitate you to get comfortable with Cloudera Manager. You will be able to sign up for GCP and avail credit up to $300 while offer lasts. Credits are valid up to year. You will then understand brief overview about GCP and provision 7 to 8 Virtual Machines using templates. You will also attaching external hard drive to configure for HDFS later. Once servers are provisioned, you will go ahead and set up Ansible for Server Automation. You will take care of local repository for Cloudera Manager and Cloudera Distribution of Hadoop using Packages. You will then setup Cloudera Manager with custom database and then Cloudera Distribution of Hadoop using Wizard that comes as part of Cloudera Manager. As part of setting up of Cloudera Distribution of Hadoop you will setup HDFS, learn HDFS Commands, Setup YARN, Configure HDFS and YARN High Availability, Understand about Schedulers, Setup Spark, Transition to Parcels, Setup Hive and Impala, Setup HBase and Kafka etc. Once all the services are configured, we will revise for exam by mapping with required skills of the exam. Who this course is for: System Administrators who want to understand Big Data eco system and setup clusters Experienced Big Data Administrators who want to prepare for the certification exam Entry level professionals who want to learn basics and Setup Big Data Clusters 👉 Activate Udemy Coupon 👈 Free Tutorials Udemy Review Real Discount Udemy Free Courses Udemy Coupon Udemy Francais Coupon Udemy gratuit Coursera and Edx ELearningFree Course Free Online Training Udemy Udemy Free Coupons Udemy Free Discount Coupons Udemy Online Course Udemy Online Training 100% FREE Udemy Discount Coupons https://www.couponudemy.com/blog/cca-131-cloudera-certified-hadoop-and-spark-administrator/

[theasphodelmeadows]

i was tagged by @punk-rat to post 10 facts about myself, thank you!! yours were very interesting!

1. I was born butt-first and apparently that’s a rare enough thing to happen naturally that my mom was surrounded by a small army of doctors in training to witness the entire thing and i’m just really glad i greeted the world that way

2. (like many of my peers) I first taught myself English playing runescape and pokemon games and I distinctly remember one of the first tasks in the runescape tutorial being ‘make a fire’ and thinking the fuck does that even mean

3. the dog we had when i was a child was called Kafka

4. i was a really big fan of the band Alesana as a young teen, i first saw them live when i was 13 and their online fanclub (which i actually paid for) was pretty much my first online community - my very first tumblr followers were actually people i met there but i haven’t listened to them in years now

5. I never thought i’d have my first kiss before i turned 20 but in the end i got my first kiss 2 months before my 20th birthday - and then kissed 2 more people before then

6. I went to secondary school in a literal castle with nuns still living there, uniforms and everything

7. Placebo was my mom’s favourite band when i was growing up and they were one of the first bands I could identify - is it any wonder i grew up to be bi lmao

8. Another favourite of my parents’ when I was growing up was Nick Cave  - they first saw him live at the first festival they ever went together in 1989 and then pretty much every time he’s come to Belgium since so I was obviously always aware of him but I didn’t care for music at all until around 2008 which happened to be the year he had that ridiculous moustache and dig lazarus dig came out which i still one of my least fave albums and then in 2009 with the death of bunny munroe that was enough to give me this image of Nick Cave as a creepy old man who only sings about murdering women and I refused to listen to him until I saw him live at a festival in 2013 and um so that changed a lot

9. I have a TERRIBLE sense of direction - I’ve actually gotten lost in my own home town multiple times. I also for some reason absolutely cannot read a clock at a glance, I really have to stare at it for a while to figure it all out

10. Some friends and I have this tradition where every time we’re together having drinks at someone’s place we’ll put on the video of Kate Bush’s Wuthering Heights and (attempt to) dance and sing along to it and it’s always very confusing for people who’ve never witnessed it before

i’m tagging @lewnixoned, @narcvis, @ket-kitten, @honeyfred, @spilling-everything, @oatmealcow, @leviathan-charm & everyone else who i forgot/wants to do it!!

[gkindexindia]

Apache Kafka Online Tutorial

Kafka is one of the messaging system, which uses the pattern of publish and subscribe messaging system.Publish is nothing but a sender and receiver is nothing but a subscriber.For every publish and subscriber system, we do often see a broker in between them.The broker here is nothing but a Apache Kakfa.

Kafka is not just a broker, its beyond the broker. Will see in upcoming chapters what other tasks can be performed by the Kafka.

Apache Kafka Installation in windows

Please follow the below steps for installing kafka in windows

Download the Apache Kafka from https://kafka.apache.org/downloads

          Extract the downloaded folder in C:\ drive

         Navigate to C:\kafka\bin\windows

         Starting Apache Kafka in windows

zookeeper first needs to be started with following command.

C:\kafka\bin\windows\zookeeper-server-start.bat C:\kafka\config\zookeeper.properties

After starting the zookeeper start the kafka with below command

C:\kafka\bin\windows\kafka-server-start.bat C:\kafka\config\server.properties

Apache Kafka Overview

Apache Kafka Features

Multiple Producers

         Multiple Consumers

        Scalable

        Cross Languages support

        High Performance

       Multiple Producers

Kafka will handle the multiple producers, unlike in many other Messaging systems. Irrespective to the number of subscribers running in the System, which helps to scalable not only in the Subscriber end and also from the producers as well.

Multiple Consumers

Kafka do support multiple consumers as well, which in turn helps the load balancing from the consumer end as well.

Scalable

kafka does support scalable as well without limiting of the Data. kafka inbuilt features helps to handle any volume of the Data.

High Performance

Considering all the features of the Kafka.Meaning that multiple producers,multiple consumers scalability will help to achive the higher perfromance.

Apache kafka Producer

In the publish and subscribe messaging system, the flow starts from the Publisher(which sends a piece of message to the broker(Kafka)).

Kafka comes with Client API , which will help to communicate with Kafka. The following is the example for the Kafka Producer, which will help you to understand how we are communicating with Kafka while sending the message(Record).

Apache Kafka Features

Multiple Producers

Multiple Consumers

Scalable

Cross Languages support

High Performance

Multiple Producers

Kafka will handle the multiple producers, unlike in many other Messaging systems. Irrespective to the number of subscribers running in the System, which helps to scalable not only in the Subscriber end and also from the producers as well.

Multiple Consumers

Kafka do support multiple consumers as well, which in turn helps the load balancing from the consumer end as well.

Scalable

kafka does support scalable as well without limiting of the Data. kafka inbuilt features helps to handle any volume of the Data.

High Performance

Considering all the features of the Kafka.Meaning that multiple producers,multiple consumers scalability will help to achive the higher perfromance.

[rafi1228]

Learn Data Science, Data Analysis, Machine Learning (Artificial Intelligence) and Python with Tensorflow, Pandas & more!

What you’ll learn

Become a Data Scientist and get hired

Master Machine Learning and use it on the job

Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0

Use modern tools that big tech companies like Google, Apple, Amazon and Facebook use

Present Data Science projects to management and stakeholders

Learn which Machine Learning model to choose for each type of problem

Real life case studies and projects to understand how things are done in the real world

Learn best practices when it comes to Data Science Workflow

Implement Machine Learning algorithms

Learn how to program in Python using the latest Python 3

How to improve your Machine Learning Models

Learn to pre process data, clean data, and analyze large data.

Build a portfolio of work to have on your resume

Developer Environment setup for Data Science and Machine Learning

Supervised and Unsupervised Learning

Machine Learning on Time Series data

Explore large datasets using data visualization tools like Matplotlib and Seaborn

Explore large datasets and wrangle data using Pandas

Learn NumPy and how it is used in Machine Learning

A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided

Learn to use the popular library Scikit-learn in your projects

Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry

Learn to perform Classification and Regression modelling

Learn how to apply Transfer Learning

Requirements

No prior experience is needed (not even Math and Statistics). We start from the very basics.

A computer (Linux/Windows/Mac) with internet connection.

Two paths for those that know programming and those that don’t.

All tools used in this course are free for you to use.

Description

This is a brand new Machine Learning and Data Science course just launched January 2020 with the latest trends and skills! Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 240,000+ engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei’s courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, + other top tech companies.

Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).

This comprehensive and project based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real world projects to add to your portfolio. You will get access to all the code, workbooks and templates (Jupyter Notebooks) on Github, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on the job skills that employers want.

The curriculum is going to be very hands on as we walk you from start to finish of becoming a professional Machine Learning and Data Science engineer. The course covers 2 tracks. If you already know programming, you can dive right in and skip the section where we teach you Python from scratch. If you are completely new, we take you from the very beginning and actually teach you Python and how to use it in the real world for our projects. Don’t worry, once we go through the basics like Machine Learning 101 and Python, we then get going into advanced topics like Neural Networks, Deep Learning and Transfer Learning so you can get real life practice and be ready for the real world (We show you fully fledged Data Science and Machine Learning projects and give you programming Resources and Cheatsheets)!

The topics covered in this course are:

– Data Exploration and Visualizations

– Neural Networks and Deep Learning

– Model Evaluation and Analysis

– Python 3

– Tensorflow 2.0

– Numpy

– Scikit-Learn

– Data Science and Machine Learning Projects and Workflows

– Data Visualization in Python with MatPlotLib and Seaborn

– Transfer Learning

– Image recognition and classification

– Train/Test and cross validation

– Supervised Learning: Classification, Regression and Time Series

– Decision Trees and Random Forests

– Ensemble Learning

– Hyperparameter Tuning

– Using Pandas Data Frames to solve complex tasks

– Use Pandas to handle CSV Files

– Deep Learning / Neural Networks with TensorFlow 2.0 and Keras

– Using Kaggle and entering Machine Learning competitions

– How to present your findings and impress your boss

– How to clean and prepare your data for analysis

– K Nearest Neighbours

– Support Vector Machines

– Regression analysis (Linear Regression/Polynomial Regression)

– How Hadoop, Apache Spark, Kafka, and Apache Flink are used

– Setting up your environment with Conda, MiniConda, and Jupyter Notebooks

– Using GPUs with Google Colab

By the end of this course, you will be a complete Data Scientist that can get hired at large companies. We are going to use everything we learn in the course to build professional real world projects like Heart Disease Detection, Bulldozer Price Predictor, Dog Breed Image Classifier, and many more. By the end, you will have a stack of projects you have built that you can show off to others.

Here’s the truth: Most courses teach you Data Science and do just that. They show you how to get started. But the thing is, you don’t know where to go from there or how to build your own projects. Or they show you a lot of code and complex math on the screen, but they don’t really explain things well enough for you to go off on your own and solve real life machine learning problems.

Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. This course is not about making you just code along without understanding the principles so that when you are done with the course you don’t know what to do other than watch another tutorial. No! This course will push you and challenge you to go from an absolute beginner with no Data Science experience, to someone that can go off, forget about Daniel and Andrei, and build their own Data Science and Machine learning workflows.

Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career.

You hear statements like Artificial Neural Network, or Artificial Intelligence (AI), and by the end of this course, you will finally understand what these mean!

Click “Enroll Now” and join others in our community to get a leg up in the industry, and learn Data Scientist and Machine Learning. We guarantee this is better than any bootcamp or online course out there on the topic. See you inside the course!

Taught By:

Andrei Neagoie is the instructor of the highest rated Development courses on Udemy as well as one of the fastest growing. His graduates have moved on to work for some of the biggest tech companies around the world like Apple, Google, Amazon, JP Morgan, IBM, UNIQLO etc… He has been working as a senior software developer in Silicon Valley and Toronto for many years, and is now taking all that he has learned, to teach programming skills and to help you discover the amazing career opportunities that being a developer allows in life.

Having been a self taught programmer, he understands that there is an overwhelming number of online courses, tutorials and books that are overly verbose and inadequate at teaching proper skills. Most people feel paralyzed and don’t know where to start when learning a complex subject matter, or even worse, most people don’t have $20,000 to spend on a coding bootcamp. Programming skills should be affordable and open to all. An education material should teach real life skills that are current and they should not waste a student’s valuable time. �� Having learned important lessons from working for Fortune 500 companies, tech startups, to even founding his own business, he is now dedicating 100% of his time to teaching others valuable software development skills in order to take control of their life and work in an exciting industry with infinite possibilities.

Andrei promises you that there are no other courses out there as comprehensive and as well explained. He believes that in order to learn anything of value, you need to start with the foundation and develop the roots of the tree. Only from there will you be able to learn concepts and specific skills(leaves) that connect to the foundation. Learning becomes exponential when structured in this way.

Taking his experience in educational psychology and coding, Andrei’s courses will take you on an understanding of complex subjects that you never thought would be possible.

See you inside the course!

Who this course is for:

Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science and Python

You are a programmer that wants to extend their skills into Data Science and Machine Learning to make yourself more valuable

Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field

You’re looking for one single course to teach you about Machine learning and Data Science and get you caught up to speed with the industry

You want to learn the fundamentals and be able to truly understand the topics instead of just watching somebody code on your screen for hours without really “getting it”

You want to learn to use Deep learning and Neural Networks with your projects

You want to add value to your own business or company you work for, by using powerful Machine Learning tools.

Created by Andrei Neagoie, Daniel Bourke Last updated 5/2020 English English [Auto-generated]

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