I recently came across a wonderful suite of materials for introducing statistical learning:
- Hastie, et al’s free textbook (link to the PDF can be found on this page).
- The accompanying lecture videos – 15 hrs in total – freely available through YouTube (outline of, and links to, the videos here).
- Additional slides provided by professor Al Sharif (here), including PDF documents of R scripts and explanations for a wide range of topics covered in the book.
To give folks a feel for the content, it addresses many of the techniques presented at the University of Queensland’s graduate-level Machine Learning course. It also addresses many of the techniques I used, along with colleagues, at Shell to help optimise their massive coal-seam gas business in Brisbane, Australia.
I’ve looked at and used a range of training resources for software engineers and machine learners. For some, the quality can be poor and the value dubious.
But one resource that really stands above the rest – this one is world class, with very high value, is the OMSCS at Georgia Tech.
If you don’t know already, OMSCS stands for the Online Masters of Science in Computer Science. Georgia Tech has partnered with Udacity to deliver courses online for those who want to study – at the post-graduate level – computer science. If you take 10 courses the will give you a MS in CS. But keep in mind it is one of the top computer science departments in the US, and is not easy.
Their mission is to make education accessible to more people, and they do so by charging the fees at cost. The entire degree costs ~US$7k.
The program is part-time – the most aggressive schedule would be 5 courses in a 12 month period – so can be completed in 2+ years.
If an engineer has some background in basic object oriented programming, networking, relational databases and some prior exposure to memory management and Python, then it should be possible to get through the course work. (Check out the OMSCS subreddit for admission stats)
At one course per semester, it would be a ~3 year effort. And would comprise a significant technical development path for any relatively junior machine learner.
Not too bad for technical development. USD$7k and 3 years, part-time!