AI in Drug Discovery: Introduction

The aim of this course is to provide learners with a simple and structured foundation in AI-driven drug discovery. It helps participants understand how artificial intelligence can support pharmaceutical research, biomedical data analysis, target discovery, molecular screening, and responsible decision-making in life science research.

By the end of this course, learners will be able to understand the basic workflow of drug discovery and the role of AI in pharmaceutical research. They will learn about biomedical and molecular data, target identification, virtual screening, drug-like property prediction, lead optimization, responsible AI use, key challenges, and future career opportunities in AI-driven drug discovery.

This course is suitable for students, beginners, freshers, biotechnology learners, pharmacy learners, life science learners, healthcare research professionals, and anyone interested in AI applications in drug discovery. It is also useful for learners from biotechnology, pharmacy, pharmaceutical science, bioinformatics, life sciences, biomedical science, chemistry, medicine, and data science backgrounds.

After completing this course, learners will be able to explain how AI is applied in drug discovery, identify the importance of biomedical and molecular data, understand basic AI-supported workflows such as target identification and virtual screening, describe drug-like property prediction and lead optimization, and explore further learning paths in AI, biotechnology, pharmacy, and pharmaceutical research.