There is tons of on-line material, tutorials and courses on ML, including Coursera lectures.

I’ll respond more specifically for deep learning. You can get a broad idea of deep what deep learning is about through tutorial lectures that are available from the Web. Most notably:

• an overview paper in Nature by myself, Yoshua Bengio and Geoff Hinton with lots of pointers to the literature: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=WLN3QrAAAAAJ&citation_for_view=WLN3QrAAAAAJ:lo0OIn9KAZgC
• The Deep Learning textbook by Goodfellow, Bengio and Courville: Deep Learning
• A recent series of 8 lectures on deep learning that I gave at Collège de France in Paris. The lectures were taught in French and later dubbed in English:
• French version: Accueil
• English version: Home
• the Coursera course on neural nets by Geoff Hinton (starting to be a bit dated).
• the lectures from the 2012 IPAM Summer School on Deep Learning: Graduate Summer School: Deep Learning, Feature Learning (Schedule) - IPAM
• my 2015 course on Deep Learning at NYU: deeplearning2015:schedule | CILVR Lab @ NYU (unfortunately, the videos of the lectures had to be taken down due to stupid legal reasons, but the slides are there). I’m teaching this course again in the Spring of 2017.
• The 2015 deep learning summer school: Deep Learning Summer School, Montreal 2015
• Various tutorials generally centered on using a particular software platform, like Torch, TensorFlow or Theano.