DeepLearning.ai Study Group 2019-2020
This is the third edition of our 12-week long advanced deep learning study series for AI enthusiasts and computer engineering students. Starting on September 28, we study the materials on https://www.deeplearning.ai each week and get together on saturdays to discuss them.
In this study group, the participants get an opportunity to interact with other participants, community members and guest professors to improve their knowledge on deep learning, apply it effectively, and build a career in AI. You will learn about Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN/LSTM/GRU), optimization algorithms (SGD, Adam, etc.), regularizers (Dropout, L1/L2, etc.), initialization schemes, and more.
We will go through programming assignments and quizzes as well as having discussions with other participants and experienced mentors.
Here are some photos taken at our first study group on deep learning last year:
Programming experience: The course is taught in Python. We assume you have basic programming skills (understanding of for loops, if/else statements, data structures such as lists and dictionaries).
Mathematics: basic linear algebra (matrix-vector operations and notation)
Machine Learning: conceptual knowledge of machine learning ( supervised learning, unsupervised learning, test data, validation, some machine learning algorithms such as linear regression, logistic regression)
Have a Python environment i.e. Anaconda ready on your computer before the programme. You will find instructions here.
FREQUENTLY ASKED QUESTIONS
See the FAQ here.
TYPICAL STUDY GROUP SCHEDULE / September 28
11:00 - 11:15 Introduction
11:15 - 13:00 Discussion
13:00 - 14:00 Lunch
14:00 - 15:00 Problem solving
15:00 - 15:15 Coffee Break
15:15 - 16:30 Discussion
You can find the full layout of our program here, please note that we will cover some of the courses in a single session (For example first week, we will cover the first two courses).
All participants have to abide by the OUR CODE OF CONDUCT.