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What’s the Best Way to Prepare for a Career in Data Science/Machine Learning?

December 26, 2020 by systems

Photo by Sergey Zolkin on Unsplash

There are a variety of options these days for MOOC offerings with some of them providing certificates to validate your learning. The key thing that I want to stress with MOOCs is that with their advent and acknowledgment by companies, it does relieve the burden of having to go through a degree-based program to make a career change. While companies may not look at a MOOC certificate the same as a four or two-year degree, if a user can demonstrate their knowledge that they gained through a portfolio of work and through their resume, this is massive for the learner. An effective, cheaper way to learn new skills to further your career.

The MOOC that I’ll be focusing on and one that I have used extensively is Coursera. I’ve used some other companies, but I really have enjoyed Coursera the most. They have tons of classes, topics, and specializations available (a collection of courses that have a particular theme). The awesome thing with Coursera is that the courses are put together by academic institutions and universities, professional organizations/institutions, as well as companies (like Google). What I have found to be good is that if you want to start building your mathematical knowledge to prepare your data science career, there are a variety of organizations and institutions that teach common material, meaning that if the methods of teaching don’t suit you you can find other courses on the same topic that match better your learning style. Through MOOC’s you can slowly build up your understanding in whatever direction you want to go into in this new field (data engineering, data science, etc…). You can also help build yourself a learning plan and schedule a sequence of courses to either be a generalist or narrow into a specialization in a particular field. Really there are a lot of great options which is why I would suggest anyone leverage MOOCs if you can. They do take up a fair amount of time to go through the lectures, assignments, etc… So be very focused in terms of what you want to learn and set a schedule to accomplish it in a specific amount of time.

Filed Under: Machine Learning

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