About this Course
GNNs on molecular graphs are how modern pharma screens billions of compounds. This comprehensive curriculum is designed to give you hands-on experience with Graph Neural Networks for Drug Discovery. This Bioinformatics & ML Researchers curriculum is designed to give you hands-on experience and deep conceptual understanding.
Across 4 intensive modules, you'll tackle real-world challenges and build practical projects that reinforce your learning. By the end of this journey, you'll have the skills and proof of work to demonstrate your expertise.
What you'll learn
Master the core concepts of molecular graph representations & rdkit.
Gain hands-on experience with message passing neural networks (mpnn).
Understand the architecture behind 3d molecular conformations & equivariant gnns.
Implement production-grade virtual screening pipeline & generative design.
W1
Molecular Graph Representations & RDKit
Master the core concepts of molecular graph representations & rdkit.
3 videos•67m
3 readings
3 topics
1 homework
W2
Message Passing Neural Networks (MPNN)
Gain hands-on experience with message passing neural networks (mpnn).
3 videos•124m
3 readings
3 topics
1 homework
W3
3D Molecular Conformations & Equivariant GNNs
Understand the architecture behind 3d molecular conformations & equivariant gnns.
3 videos•65m
3 readings
3 topics
1 homework
W4
Virtual Screening Pipeline & Generative Design
Implement production-grade virtual screening pipeline & generative design.
3 videos•101m
3 readings
3 topics
1 homework
01
Learn
Watch curated videos and read study resources
02
Practice
Practice what you learned
03
Build Projects
Build projects using your new gained knowledge
04
Submit & Verify
Submit your project and get verified by our system
References
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