If you’re just getting into data science, it’s easy to feel overwhelmed. Did you waste all that time in college for nothing? Are you going to be far behind everyone else? What happens if you don’t love it after all? Making a career change at any stage is scary, but these days it doesn’t have to be. We’ve got online learning.
Countless universities and businesses have dedicated themselves to making free education more accessible—especially if you don’t need the piece of paper. You can still get certifications, and actually learn something about data science without even touching your credit card.
The reality is, so much of job skills today aren’t based on what you studied—it’s about what you’ve learned. That comes from job experience, self-directed teaching, and the genuine curiosity needed to become an expert. If you’ve got a single motivated gene in your body, that’s all you need to master data science.
It’s not always going to come easy, but there are terabytes of ebooks, whitepapers, video lectures, and courses out there designed to make it as straightforward as possible. This list below singles out 8 different courses that you can start with to master the ins and outs of data science. Along the way you’ll find yourself starting to talk the talk, really understand more of the articles and blogs you’re reading, and have something to contribute as you seek out new positions in the data science realm.
Check out any and all of these courses, and set yourself on the path to being a data science master today! Good luck!
Introduction To Data Science – Jeff Hammerbacher, UC Berkley
This course is exactly what it sounds like: an introduction. It covers five different areas of data science: preparation, presentation, products, observation, and experimentation. This course follows a real-time college schedule, complete with coursework, exams and guest speakers. For that alone, this is definitely something worth diving into with everything you’ve got.
A lot of learning is simply what you make it. If you’ve got the time to invest, then you’re going to learn a lot. If you don’t have the time, then taking a course like this is ultimately going to be more wasteful. There are plenty of courses on this list that are more flexible. Keep feeling around until you have the right fit for you.
Introduction To Data Science – Bill Howe, University of Washington
This one’s an alternative to the first introductory course. It incorporates a solid business understanding of the utility of data science, helping to give you a bit of a crash course in all the essentials: from algorithms, to mining, management, and modeling
Per Coursera’s information, it’s an 8-week course that requires about 10-12 hours per week of your time. While that may seem like a heavy commitment, you have to think about it in parcels: 2 months of spending 2 hours a day on a course, to get a very solid foundation in the world of data science. If you’re serious about this, it’s worth it. Especially since it’s free.
Introduction To Data Mining – Nitin Patel, MIT
Who wouldn’t want to take a course from MIT? Now that you’ve got some of the basics down with an introductory overview, it’s time to work on more of the nitty-gritty. Data mining is certainly something that deserves it’s own course, and the Sloan School of Management is a great place to start.
Keep in mind that this course is from 2003, but it still provides an excellent framework for data methods that we use even today. Use it as a foundation to further studies into data mining, or a framework to inform other areas of study.
Getting and Cleaning Data – Jeff Leek, Johns Hopkins University
As the introduction to this course reads: “Before you can work with data you have to get some.” The reality is that while there are plenty of places to grab external, third-party data, that’s not what’s going to make you a master. You have to learn what to do when you need to get a ton of data and be able to sift through it—clean it, as the title implies.
The whole purpose of this course is to teach you tactics for acquiring data from a number of different sources, and using them for your own analysis. This course will lay the foundation for working with data in the same myriad of ways companies do. It will empower you to be an innovator, not just someone who can bend what others have wrought.
Pattern Discovery in Data Mining – Jiawei Han, University of Illinois at Urbana-Champaign
This course is one of a handful of courses which you can use to work towards a certification through Coursera—something that can definitely help make you more appealing for either a new hire or promotion within your own company. In the spirit of encouraging you to be proactive, we won’t outline every single one of those courses here, but this one is a great one-off to start from.
While data mining can certainly come naturally for some—others might discover it to be a bit of a foreign language. Don’t let that intimidate you, this course is here to help. You’ll be taught, as the name implies, to recognize the patterns in data, and program your brain to think like a real data miner.
Data Visualization – John C. Hart, University of Illinois at Urbana-Champaign
This is another course in that series for Coursera certification. There’s truly art to data, and it comes mostly in visualization. When you have such a mastery of data that you can actually produce creative ways of expressing it, that’s when you know you’re truly on the road to being a master.
In that sense, this is your master class. Understanding digital visualization is certainly one thing, but being able to apply that skill is another. If you can produce solid data visualization, you’re going to be indispensable at any organization that’s dealing with data.
Applied Data Science – Multiple Instructors, Syracuse University
Here’s another straightforward course in the practical application for data science. If you’re someone who’s already in a job, and looking to adapt quickly to the changing data climate, then this course has got your back.
What’s especially nice about this course is that it works at your pace, following along with an eBook, while backed by the solid name of Syracuse. If you’re feeling pressed for time, but still need a solution, this course may become your go-to.
Big Data Applications and Analytics – Geoffrey Fox, Indiana University
Finally, you need a course that touches on the buzzword of the year: big data. This course allows you to touch on some relevant topics like the Netflix recommendation system, and gives you a big picture of what the cloud is doing for big data right now.
Whatever course or courses you ultimately end up taking, remember: it’s on you. You can make these classes feel like a free time-waster, or give them value that will stretch the length of your career.
Bonus: Pretty much everything – Udemy and Code School
If full on University courses sound a bit much for you or you want something less generic, there are plenty of shorter online courses you can take for free (or a small fee) on Udemy and Code School. You can learn anything from programming in R, data collection, visualization techniques and more.
What other courses should be on this list? Let us know in the comments section!
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