Drug Discovery ML Course Index — Dataplexa

Drug Discovery ML

Drug Discovery ML
Course Index

30 Lessons · 3 Levels

ML for computational drug discovery in Python — RDKit molecular featurization, QSAR models, DeepChem GNNs, AutoDock Vina docking, and generative AI for novel molecules. Covers AlphaFold, federated learning, FDA/EMA/CDSCO regulations & 4 real drug discovery builds.

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30Lessons

3Levels

4Projects

FreeAccess

Level ICheminformatics & Drug Discovery FoundationsLessons 1–10

Drug Discovery ML: Overview

Drug Discovery Pipeline & Stages

Python & RDKit for Cheminformatics

SMILES & InChI Representations

Fingerprints & Descriptors

ChEMBL, DrugBank & PubChem

Bioactivity Data: IC50, EC50 & Ki

ADMET & Lipinski Rules

Virtual Screening Workflows

Molecular Docking: AutoDock Vina

Level IIML & Deep Learning for Drug DiscoveryLessons 11–22

QSAR Structure-Activity Models

ML for Bioactivity Prediction

Graph Neural Networks for Molecules

Deep Learning with DeepChem

Generative AI for Drug Design

AlphaFold for Target Structure

Protein-Ligand Interaction

Drug Repurposing with ML

Target ID & Omics Integration

Clinical Trial Outcome Prediction

Toxicity Prediction Models

LLMs in Drug Discovery

Level IIIAdvanced Topics, Regulations & ProjectsLessons 23–30

Federated Learning

Drug Regulations: FDA, EMA & CDSCO

MLflow for Drug Discovery Models

AWS & GCP for Drug Discovery

Build a QSAR Bioactivity Predictor

Build a Virtual Screening Pipeline

Build a Molecular Generative Model

Build an AI Drug Repurposing Tool

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Drug Discovery ML Course Index

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