Deep Learning Certificate Part II
This course will be held online in Spring 2020.
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.