Why I like Stanford’s Online Machine Learning Course for Training
The University of Washington is making a big push for additional funding to support UW Computer Science and Engineering. Some people have suggested doubling the funding to increase the number of graduates per year by less than a thousand.
I’m skeptical, but mostly because I think integrating courses like Stanford’s online machine learning courses into someone’s job will result in better outcomes for students. Stanford’s course is much lighter than a typical undergraduate or graduate course on machine learning, but it may be more useful. It establishes a common set of code, cases, and vocabulary around machine learning and it is unobtrusive enough for a programmer working at a large company or a startup to do each week and still have a full time job. The “assignments” become integrating the lessons learned into the company’s business.
If we coupled this type of learning with a certification program, it would be more valuable for students and industry than taking a student out of the work force and asking them to spend a lot of time commuting (or living) in an undergraduate or graduate program. The learning could be more integrated with their job. And the loss of income/cost of education would be especially tasty for young people that have become over-burdened with debt from the modern American university system.
This won’t work for everyone, but for most tech workers, it should work much better than the current system.
