In recent weeks, you might have found yourself working from home and with a bit more time on your hands than usual. In case you’d like to spend that time upskilling your work-related talents, we’ve pulled together a list of some of the best online courses and certifications available. As these are all 100% online, you won’t need to acquire new expertise.
Since you’re reading this on RapidMiner’s blog, chances are that you’re at least interested in data science, if you’re not actually responsible for it on some level at your organization. So this post will focus specifically on some of the top data science-related courses that are available online.
Top 8 online courses for learning data science
Some of these online courses are free, some have fees; some you can start any time, and others you need to sign up at a specific point. Click through to each individual resource below for the details.
If you’re completely new to data science, but have a working knowledge of statistics and probability, EdX (an online teaching and learning platform developed by Harvard and MIT) offers a variety of data science courses some of which even result in professional certificates to show off your knowledge and enhance your resume. Costs for these courses vary based on the length and provider
Geared towards professionals who want to develop their skills, Udemy has lots of courses for learning about data science, including topics like the basics to specific languages (e.g., Python) and individual platforms (e.g., Tableau). Udemy’s teachers aren’t necessarily affiliated with universities, with many coming from the business world.
We can’t ignore our own learning platform, RapidMiner Academy. We take a ‘micro-modular’ approach to our courses, offering just-in-time courses that teach you what you need to know when you need to know it. We cover data science topics and, unlike many of the other offerings discussed here, we also leverage our knowledge of business uses for data science to help our learners better understand the specific applications of data science to business. Plus, our Academy is totally free!
While mostly focused on individual courses for specific computer languages, CodeAcademy also lets students string together a series of related courses that will amount in the end to solid knowledge of data science topic and techniques. Courses at CodeAcademy include Python and SQL.
Offering courses across a wide spectrum of topics, both free and paid, Coursera students can earn everything from completion certificates, to higher level professional certificates all the way to online degrees. Coursera allows students to learn data science through this same variety of levels, and includes courses from providers like IBM and the University of Michigan.
Udacity is a paid platform with mostly tech-related offerings. They have a wide selection of data science courses and what they call ‘nanodegrees’. Udacity maintains that they have a specific focus on helping their students build relevant skills and project portfolios to enhance their careers, and offers a spectrum of data science courses and programs.
8. Khan Academy
If your middle school or high school kids are also stuck at home, Khan Academy’s courses may be a way to help them learn a little about what their parents are interested in. Khan Academy helps students study for AP tests, and includes courses that discuss data science, especially as it relates to Advanced Placement Computer Science courses.
Note that this list isn’t meant to be comprehensive of every online learning tool but is just intended to highlight some of the big players. Many other organizations are putting materials online, including traditional universities and colleges like Harvard, which means there are a lot of options to explore.
If reading is more your speed, you can also check out our latest whitepaper, A Human’s Guide to Machine Learning Projects, which walks you through the process to make sure your machine learning projects are a success.
On this episode, Ingo welcomes in the New Year by talking through the opportunities and challenges facing big data analytics professionals around the world.