Machine Learning in Drug Discovery and Cheminformatics

Welcome to Machine Learning for Drug Discovery & Cheminformatics This course is designed for all levels, from beginners who are new to programming and machine learning, to intermediate learners who want to apply AI in real drug discovery workflows. You will learn how to combine Python, Machine Learning, AI, and Cheminformatics to build practical solutions used in modern computational drug discovery. What You Will LearnPython fundamentals for scientific computingData handling and preprocessingMolecular representations (SMILES, molecular fingerprints)Building and evaluating Machine Learning modelsUnderstanding R², RMSE, and model performanceVirtual screening workflowsADMET filtering conceptsHow to build real-world drug discovery projects Practical, Project-Based ApproachThis is not a theory-only course. You will: Build real Machine Learning Project in Cheminformatics modelsBuild real QSAR modelsGenerate molecular fingerprints using RDKitPerform virtual screening on compound librariesApply AI to predict biological activityBy the end of the course, you will understand how machine learning is applied in real computational drug discovery pipelines. Who This Course Is ForPharmacy students and PharmacistsChemistry and life science studentsBioinformatics and cheminformatics learnersData science students interested in healthcareAnyone who wants to apply AI in drug discoveryAfter This CourseYou will be able to: Start your own drug discovery ML projectsUnderstand pu