Deep Learning Certificate Part II
This course follows on from (and requires completion of) part 1 (and the associated MOOC). It tackles more complex problems that require integrating a number of techniques. This includes both integrating multiple deep learning techniques , as well as combining classic machine learning techniques with deep learning. All methods will be introduced in the context of solving end-to-end real world modeling problems.
We're pleased to announce that Chris Lattner, the inventor of Swift, will be joining Jeremy for the last 2 lessons, to help teach Swift for TensorFlow.
Prerequisites
- familiarity with Python, git, and bash
- familiarity with the content covered in Deep Learning Part 1, version 2, including the fastai library, a high-level wrapper for PyTorch.
- attend in-person Monday evenings at our Downtown campus
- commit 10 hours a week to course study
The deep learning, the fastai library, and PyTorch requirements can be fulfilled by:
- completing the updated, in-person Deep Learning Part 1 course (first offered fall '17)
- completing all 7 lessons of part 1 of the MOOC at course.fast.ai
| Details | |
|---|---|
| Dates | TBA |
| Schedule | TBA |
| Location | 101 Howard St. San Francisco, CA |
| Instructors | Jeremy Howard |
| Continuing Education Units | 1.5 |
| Cost | $2000 |
Contact Info
The Data Institute
Mon-Fri, 9 a.m. - 5 p.m.