Hands-on program for developers familiar with the basics of deep learning
There are great online courses on how to train deep learning models. Some start with theory, some start with code. But training the model is just one part of shipping a complete deep learning project. Our course is aimed at people who already know the basics, and want experience with the full stack.
Attendees will learn and get first-hand experience with best practices of all components of a deep learning project:
Attendees will spend 30% of the time on developing and deploying a state-of-the-art computer vision and natural language processing system.
Those on the job market can choose to take a certification exam, aimed to ensure that you are ready for deep learning engineer technical interviews. The exam covers pre-requisites as well as course content, and can be taken on your own time.
Professor at UC Berkeley, President of Covariant.AI
Director of AI at Gradescope
Research Scientist at OpenAI
Director of AI at
Previously Research Scientist at OpenAI
Director of Product at
Previously Senior Director of Product at Cloudera, Senior Product Manager at VMWare
Developed the Caffe framework at UC Berkeley, helped develop Tensorflow at Google
Weights & Biases
Previously founded Figure Eight (Crowdflower)
Any time within 4 weeks of the bootcamp, attendees can choose to take the certification exam, aimed at showing requisite knowledge for the position of deep learning engineer. A study guide will be part of the program materials.
The bootcamp will be held Friday-Sunday August 3-5, 2018 on UC Berkeley campus. The three-day bootcamp cost is $2450, with a discount for students.
At most 150 people will be admitted to the program. We will carefully read every application. Admission will be on a rolling basis, so applying earlier will improve your chances.
Update (July 10): The event is officially full. Feel free to fill out the application to be first in line regarding any future offerings! Or simply sign up for opportunities at https://fullstackdeeplearning.com.