Welcome to the asynchronous deep learning bootcamp! This course is asynchronous, so there are no set meeting times for lectures. The way the course will work is the following: 

1. You will read through the corresponding fastai chapters (http://github.com/fastai/fastbook) for a particular lesson on your own.

2. You are encouraged to form your own group to have weekly discussions based on the assigned readings (see the calendar link below). Those meetings will be used to ask each other questions and to spark discussion about applications of deep learning in data science careers. 

3. You will form teams to create a final deep learning project, which will be **due on May 03, 2024**. You must submit a final project to receive a deep learning certificate. 

Please note that all of the materials in this course are based on the content in Jeremy Howard and Sylvain Gugger's fastai course (http://course.fast.ai) and corresponding fastai book (http://github.com/fastai/fastbook). 

The copyright of the fastai material is: @book{ howard2020deep, title={Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD}, author={Howard, J. and Gugger, S.}, isbn={9781492045526}, url={https://books.google.no/books?id=xd6LxgEACAAJ}, year={2020}, publisher={O'Reilly Media, Incorporated} } 

The notebooks in the Erdős GitHub repo contain summaries I created of the fastai content in order to consolidate the material and serve as a good review.