Helpful Tools/Courses

Below are links to a couple courses/resources I have found helpful.

Coursera - Data Mining Specialization (University of Illinois - Urbana Champaign)
I completed this specialization in 2015.  My personal opinion about this coursework is that it was very theoretical for most of the classes.  Then during the capstone class, it got VERY hands-on very quick.  If you're not ready for that kind of a hockey-stick learning curve, I'd suggest one of the other programs below.  Also, the toolset that they provide for this course is not really industry standard.  I bucked the trend and completed my capstone project in R instead.

Coursera - Data Science Specialization (Johns Hopkins University)
I've taken the first couple of courses from this specialization.  This program seems to have a very good balance of theory and incremental practical learning.  When I get some more time I'll probably come back to this one and complete the rest of the courses.  The tool set is all in the R language.  If you're more of a Python programmer, see the next class below.

Udacity - Machine Learning Nanodegree
I finished this program in 2016.  Much like the Data Science Specialization above, this coursework does a good job blending theory and practice, but using Python instead of R.  The other major benefit of this program over the Coursera course is that it includes some great mini-courses on writing your data science resume, LinkedIn profile, and Git/GitHub.  They even just added a technical interview course and project.  I liked this program a lot, but for someone like me, who had already taken several classes on Coursera about data science, some of the earlier lectures and projects were very simple.  Regardless, the capstone project is pretty free-form and lets you use your creativity to get into any aspect of machine learning you're really interested in.