Then you might actually want to start in Matlab / Octave with Mchael Ng's coursera course on ML.
I completed it and can't recommend it more highly. It is a really excellent, dense course and Ng is a very good teacher.
His choice of Octave/MatLab simplifies issues of dependencies. In particular the soft ones of documentation and community. This is something a lot of academic contexts get wrong with software: the tools are either to open ended and students wind up manipulating matrices with forloops or there's an inflexible stack of professional tools that require massive effort to learn and an orthogonal community or there is a toy IDE based on a senior thesis.
Octave more or less follows the Unix philosophy of doing one thing and thus can meet many people where they are rather than with a one true way.