Course Name: Machine Learning in Bioinformatics

Faculty Name: Dr. Abhishek Subramanian

Course Period: 27 ^th Jul to 5 ^th Oct 2026 (Every Monday from 6.00-7.30 PM IST)

Number of Credits: 2 credits

Prerequisite: Familiarity with Python / R programming, basic understanding of descriptive statistics and probability, familiarity with biological high throughput omics datasets / databases

Course Contents:

Theory: Introduction to statistical learning: classification and regression problems, concepts of features and instances, supervised and unsupervised clustering approaches; Unsupervised ML algorithms: Hierarchical clustering, K-means clustering, density-based clustering; Supervised ML algorithms: logistic regression, artificial neural networks, support vector machines, decision trees & random forests; Feature selection: principal component analysis, SVM-RFE; Performance metrics: accuracy, sensitivity, specificity, precision, recall, F1-score, Mathews correlation coefficient; Introduction to Multi-class learning; Introduction to deep learning concepts

Lab: Supervised and unsupervised clustering with toy examples. Programming for machine learning classification and regression using Python / R programming

What you'll learn: This course is an introductory course to machine learning concepts, suitable for bioinformaticians / biologists with basic data analysis experience. Students will get exposed to the most popular ML tools used for various biological problems with focus on data visualization rather than the core mathematics of these algorithms that will help them choose the appropriate approach for various applications.

Fee: Rs. 10,000/- Plus GST

Payment Link: Click here

Apply here: Apply Here

Last Date for Registration and Payment: 17th July 2026