This course serves as a gateway to quantitative biology. It equips students with the essential statistical reasoning and practical programming skills needed to design experiments, analyze complex biological data, and rigorously interpret results. We move beyond theory to tackle real-world case studies from genomics, clinical research, and systems biology, providing the foundational toolkit for any student in data-driven life sciences.

This foundational course explores the "operating system" of life. We delve into the mechanisms of heredity, gene expression, and genome regulation. Understanding this core biological "language"—from DNA replication to the complex genetic pathways involved in disease—is essential for students who will go on to build the next generation of computational models to understand health, drug action, and evolution.

This course is tailored for postgraduate students in Data Science & AI (PGDDSAI) and Digital & Sustainable HCS (PGD-DSHCS). It provides the essential mathematical framework for building, understanding, and critically evaluating modern machine learning and AI models. We focus on probabilistic reasoning and statistical inference, the bedrock upon which all data-driven discovery—from computational biology to digital health—is built.