This talk covers the various data science, ML & AI massive open online courses (MOOCs). I'll talk about my experience with these MOOCs from 2011 to 2017. What should I look for in a MOOC? How do I best utilize my time learning data science, ML & AI? We'll delve into what some MOOCs did better than the others and pass on a few tips so you can effectively use these MOOCs to learn about the field.
Since 2011, beginning with ml-class and ai-class, MOOCs have spread over the years to many different topics with various organizations running them. In this talk, we will talk about the different ways in which these MOOCs explain topics in data science and contrast their pedagogical tools with each other. What course makes sense for me if I learn better visually? What course can give me the most hands-on experience? Why is the number of students a MOOC has not a great indicator of its quality? These are some of the questions we'll delve into.