Fast.ai Deep Learning Course

Next up in our Boulder Data Science course curriculum: Deep Learning (http://course.fast.ai/)!

Many of us have recently finished working thru Intro to Statistical Learning (https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about) and/or Andrew Ng's classic Machine Learning course (https://www.coursera.org/learn/machine-learning), and with that foundation of knowledge we're ready to dive into deep learning neural networks.

About the course

Course page: http://course.fast.ai/ (http://course.fast.ai/index.html)

The course takes a hands-on approach to building and analyzing neural networks using the python/keras/theano stack. From the first week you'll be building state-of-the-art models and using them to enter kaggle (http://www.kaggle.com) competitions. It's a relatively fast-paced course, but it doesn't assume any pre-reqs except for some coding experience. The course covers CNN's and RNN's and all the cutting-edge techniques used by top deep learning practitioners.

Schedule

We'll be going thru the course at a rate of 1 lesson every 2 weeks (lots of material to cover). So the (tentative) schedule looks like:

April 24 & May 1: Lesson 1
May 8 & 15: Lesson 2
May 22 & 29: Lesson 3
June 5 & 12: Lesson 4
June 19 & 26: Lesson 5
July 3 & 10: Lesson 6
July 17 & 24: Lesson 7

Everyone is welcome to attend! Come join us as we explore the state of the art in deep learning technology!