Machine Learning for Drug Discovery: Concepts to Applications (Online Workshop)
Empowering Drug Discovery with the Intelligence of Machine Learning
17–20 April 2026 | 6:30 PM IST | Online Live Workshop | Certificate
About the Workshop
This workshop provides a comprehensive introduction to machine learning (ML) in drug discovery, focusing on how computational models can accelerate and optimize the drug development process. Participants will explore how ML helps in predicting molecular interactions, analyzing biological data, and designing effective drug candidates.
Through live sessions and real-world case studies, learners will gain practical experience in building, training, and evaluating ML models tailored for bioactivity prediction and drug discovery applications.
What You Will Learn
Fundamentals of machine learning concepts and workflows
Feature extraction, selection, and data partitioning
Building and evaluating ML classification models
Understanding model performance metrics
Application of ML in bioactivity prediction and drug design
Working with bioinformatics datasets (GEO, PubChem)
Hands-on experience with Weka and feature extraction tools
Course Features
E-Certificate
Live & Interactive Sessions
Session Recordings
Protocols & Lecture PPTs
Software & Tools Support
Hands-on Training
24×7 Support
Learning Outcomes
Understand core machine learning principles for drug discovery
Build and evaluate ML models for biological data
Apply ML techniques to predict compound bioactivity
Gain practical exposure to real datasets and tools
Develop skills relevant for computational biology, pharma & biotech roles
Who Can Join
Students in Biotechnology, Bioinformatics, Life Sciences, Pharmacy, Computer Science
Researchers interested in AI/ML in healthcare & drug discovery
Beginners looking to enter computational drug discovery
Professionals in biotech, pharma, or data science domains
Course Fee
Indian Participants: ₹999 INR
International Participants: $40 USD
Workshop Module
Day 1: Introduction to Machine Learning – Part I
Basics of Machine Learning
Feature Extraction & Feature Selection
Data Partitioning
Hands-on: Introduction to Weka
Day 2: Introduction to Machine Learning – Part II
Classification Algorithms
ML Model Development
Model Performance Evaluation
Hands-on: ML Model Building using Weka
Day 3: Applications in Drug Discovery
Bioinformatics Datasets in Drug Discovery
ML Model for Biological Activity Prediction
Tools & Hands-on: GEO, PubChem, aDEL, Weka