Graph ML and deep learning courses

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Geometric Deep learning course
AMMI21
👨‍🏫 Teachers: Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Veličković
📚12 lectures, 2 tutorials, and 4 seminars
This course follows GDL BOOK
🔗 Course link: https://geometricdeeplearning.com/lectures/

Machine Learning for Graphs and Sequential Data (MLGS)
by Stephan Günnemann
Awesome course covering in depth generative models, robustness, sequential data, clustering, label propagation, GNNs, and more
🔗 Course link: https://www.in.tum.de/daml/teaching/mlgs/

Stanford CS224W course on graph ML
A legendary Stanford CS224W course on graph ML now releases videos on YouTube for 2021
🎬 60 Videos
⏰ 30h
🔗 Course link


Python For Data Science (Udemy)
This course specifically created for Data Science / AI / ML / DL. It covers BASICS PYTHON ONLY
Rating ⭐️: 4.1 out of 5
Students 👨‍🎓: 65,523 students
Duration ⏰: 3hr 55min of on-demand video
🔗 Course link

Deep Learning Prerequisites: The Numpy Stack in Python V2 (Udemy)
Rating ⭐️: 4.6 out of 5
Students 👨‍🎓: 34,785
Duration ⏰: 1hr 59min of on-demand video
🔗 Course link

There is also this cool blogpost by Gordić Aleksa:
How to get started with Graph Machine Learning

And one early access version book:
Graph Powered Machine Learning
by: Allesandro Negro
🔗 Book link

#graphML #ML #machinelearning #deeplearning #python
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