Want to learn data analysis?

Try any of our interactive data scientist training tutorials below! Regardless of your current skill set, our wide variety of data science courses will allow you to utilize an array of programming languages and techniques to extract meaningful insights from your data. We work with the ​best instructors in the world from industry and academia to deliver a comprehensive course offering.

R Programming

Master R, the leading programming language in statistics and data science. R delivers you a better and more user-friendly way to do data analysis, statistics and graphical models. No surprise it is rapidly becoming the lingua franca for data analysis in both research and enterprise settings.

Python Programming

Adding Python to your toolbox will boost your versatility and bring you closer to becoming a true data scientist. It is one of the most established general-purpose programming languages within the data science community, and an excellent language to start with if you have no prior programming experience. Our courses teach you the fundamentals of python programing all in the context of data science, keeping you focused on the essentials.

Data Manipulation

Data manipulation techniques allow you to prepare your data for further analysis without fundamentally changing the data itself. By mastering these techniques you can make your data more readable and organized thereby opening the door to perform better preparatory and exploratory data investigations. Learn how to deal with small and big data sets, and get the fundamentals on writing computational efficient code.

Data Visualization

Building a strong data visualization skill set is not only essential for communicating key data insights, it is also a strong asset when you need to uncover trends that are not necessarily visible in purely text-based data. Discover in our courses how you can produce meaningful and beautiful data visualizations, and learn yourself how to make complex exploratory and explanatory plots.

Reporting Results

Share your data analysis insights with friends, colleagues and even the rest of world via reproducible reports. Learn the techniques of dynamic reporting, and create reports that update in real time as the data changes. Even see how to export your data science results and code base to PDF, Microsoft Word and the web.

Machine Learning

By studying machine learning you will learn how you can nicely interweave statistics with computer science. Whether you want to build your personal recommendation engine, become better at picking stocks, or develop your own self-driving car, machine learning is essential. Learn the most effective machine learning techniques, and see how you can implement these yourself.

Probability & Statistics

In the Probability & Statistics topic, you will focus on the statistical techniques used to analyze and gain insights from your data. This is where the magic happens! These courses will take you from basic statistics all the way to machine learning concepts such as supervised and unsupervised learning. You'll learn how to build your own prediction models and models all from a tab in your browser.

Applied Finance

Learn how to wrangle and analyze financial data from the best instructors in the industry. It is essential to use the proper tools while applying financial theory and econometrics to the real world. These courses cover topics like portfolio analysis, time series modeling, credit risk evaluation, and much more.

Importing and Cleaning Data

Learn how to import and clean your datasets. Today, you can import data in so many different formats (csv, json, txt, etc.) and from so many different places (websites, databases, etc.). As an aspiring data science professional you need to make sure you know how to do this as efficient, effective and maintainable as possible. Once you have the data imported, chances are high you will face data that is either very raw, missing values and/or lacking clear variable names. That's why you need to learn how, regardless of source, you can clean your data so you always end up with usable and relevant data.

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