Online or In Class? Stanford’s Statistical Learning Online vs. University
After having taken the Statistical Learning course from Stanford and also a university course that was about the same material I am going to review and compare both courses. Let’s jump into the analysis of Stanford’s statistical learning online vs. university.
What we are going to cover:
- Some Background
- Lectures vs. Online Videos
- Tutorial vs. Video Labs
- Comparing the Testing of Knowledge
- Conclusion
Let’s get started!
Stanford’s Statistical Learning Online vs. University – Some Background
I am a 4th-year statistics major at a Canadian university and I took Stanford’s online course last summer in preparation for my upper-level university course. The courses were quite similar except that one was for free and the other one cost me $2000 (I am an international student). However, both courses were definitely worth it and I would encourage everyone who is going to a university to take a machine learning/Statistical Learning course as it is highly applicable to the real world.
Stanford’s Statistical Learning Online vs. University – Lectures vs. Online Videos
So, let’s dive into my review. First, the lecture style of my university course and the online course were quite similar. I read some reviews where people were complaining that Trevor Hastie and Robert Tibshirani read too much of the lecture slides. However, in a regular university course, this is not any different and the lecture serves more as a review of what one should have studied at home on their own. The lecture slides of both courses were also very similar, and I consider Trevor Hastie’s and Robert Tibshirani’s lecture slides as pretty strong. Definitely print them out and use them while going over the actual chapters in the book. One little advantage of my university course was that my professor included R code in his lecture slides which were pretty helpful as opposed to only looking at an output without code.
Stanford’s Statistical Learning Online vs. University – Tutorials vs. Video Labs
My tutorials are basically equivalent to the labs from the book that occurred after every chapter. I really liked the lab as they use small and simple data sets where one can apply the theoretical knowledge learned in the chapter. My tutorials were a bit longer and we went over theory and code which was really helpful for assignments and midterms.
Stanford’s Statistical Learning Online vs. University – Comparing the Testing of Knowledge
A significant disadvantage of the Statistical Learning course, compared to my university course, was the testing on the material. The Stanford course has one or two multiple-choice questions after every video lecture, whereas my university course demanded assignments (assigned from textbook questions), quizzes, a midterm, and a final. Through these tests, I got very familiar with the material and it helped me a lot to understand the methods better. For someone who is taking the online course, I would recommend doing some of the exercises at the end of each chapter. They are very helpful and there are tons of solutions online for someone to double-check their work. (I obviously did not do that for my assignments :). Another little advantage of my university course is being able to go to office hours of the professor and TA. However, Google is very helpful too and one can get the same answers from there!
Stanford’s Statistical Learning Online vs. University – Conclusion
In conclusion, there are no big differences comparing my university course and the online one. Both courses were very helpful and the Statistical Learning course I took in university is until now my favorite and most valuable course I have taken so far. However, it is not necessary to go to university in order to get an education. Nowadays, there are tons of learning resources online and one can get the equivalent of a university degree online (in terms of knowledge, unfortunately not in terms of recognition). So, I highly encourage everyone interested in statistics and data science to do the Stanford online course. Good luck and have fun with it!
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