POSTGRADUATE DIPLOMA IN BIOINFORMATICS
POSTGRADUATE DIPLOMA IN BIOINFORMATICS
(Hybrid Programme)
(Hybrid Programme)
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About the Programme
About the Programme
Postgraduate Diploma in Bioinformatics is a one-year programme integrating the understanding of biological data with Computational methods for Data Analysis. The incorporation of machine learning concepts has improved the comprehension of vast and complex biological data in the past few years. The PG Diploma programme is designed to provide enthusiastic biologists with the necessary foundation to utilize the wealth of available biological data for knowledge discovery. The objective of this programme is to empower young minds with tools and techniques in basic and advanced biological data analysis and become key drivers of data and precision-driven Biological Research and Industry.
Programme Overview
Programme Overview
A one-year diploma programme designed for aspiring bioinformaticians that integrates biological data analysis with computational tools for cutting-edge research and industry applications. The main focus is on machine learning, drug designing, structural bioinformatics, and next-generation sequencing (NGS)
Highlights of the programme
Highlights of the programme
Industry aligned curriculum in Bioinformatics, NGS, Multi-Omics, AI & Drug Discovery.
Hands-on training in Python, R, Biopython, databases, bioinformatics tools, and computational workflows.
Expert led sessions by academicians, researchers, and industry professionals.
Practical exposure to genomics, molecular docking, machine learning, and biological data analysis.
Problem-based learning through assignments, case studies, and capstone research projects.
Interactive webinars, workshops, and software-based training sessions.
Flexible blended learning with application oriented practical training.
Course module overview:
Course module overview:
Module 1: Bioinformatics & Programming Foundations
Fundamentals Biological concepts
Programming concepts (Python and Biopython )
Algorithms
Linux shell scripting, Bash
HPC cluster usage, Remote server workflows
Module 2: Biological Databases & APIs
Biological Databases - Exploration , data retrieval
SQL
API-Based Data Retrieval
Biological Data Processing, data visulization (Power BI)
Module 3: Sequence & Evolutionary Analysis
Sequence Alignment
MSA
Phylogenetics
Mutation Analysis
Module 4: R programming and Biostatistics
Framework for statistical analysis of biomedical data
Hypothesis Testing
Regression
PCA
Clustering
Module 5: Structural Bioinformatics
Structure prediction
AI based Protein Structure Prediction - AlphaFold
Molecular Dynamics simulation
GROMACS , DESMOND
Module 6: AI-Driven Drug Discovery
Molecular Docking
Virtual Screening
QSAR
ADMET Prediction
Module 7: Multi-Omics & Systems Biology
Single-Cell Omics
Transcriptomics
Metagenomics
Network Biology
Enrichment analysis
Module 8: NGS & Genomic Informatics
RNA-Seq
Biomarker discovery
Genome Assembly
ChIP-Seq
Docker / Singularity, Git & GitHub
Module 9: AI, Machine Learning & Biomedical Data Science
Classical ML, Visualization
Scikit-learn
Deep Learning
Keras
Cloud Computing
Big Data Analytics
Module 10: Capstone Research Project
Interdisciplinary Research
Bioinformatics Problem Solving
Scientific Reporting
Course Assessment
Course Assessment
Case Studies: Analysis of contemporary research problems and bioinformatics applications.
Coding & Workflow Assessments: Evaluation of programming, data analysis, and reproducible computational workflows using Python, R, and bioinformatics tools.
Presentations: Communication of analytical methods, results, and scientific interpretations.
Module-Based Mini Projects: Practical hands-on projects focused on individual modules and computational techniques.
Research Literature Review: Critical analysis and interpretation of recent scientific publications in bioinformatics and computational biology.
Capstone Research Project: An interdisciplinary project integrating multiple modules to address a real world bioinformatics problem, culminating in a research report and presentation.
Eligibility and Admission Criteria
Eligibility and Admission Criteria
Students who have completed a Bachelor’s Degree, B.Tech, or M.Sc. in Biological Sciences or allied life science disciplines, B.Tech / M.Tech / B.Pharm / M.Pharm programmes in relevant fields.
Students currently pursuing the 4th Year of a B.Sc. Honours programme ( Major or Minors in Biological science), M.Sc. (I or II Year) Mtech, M pharma
Ph.D. scholars pursuing research in Biological Sciences, Chemcial sciences, and allied areas.
Working professionals seeking career advancement, skill enhancement, or upskilling in the field of Biological Sciences and related disciplines..
Total No of seats: 40
Course schedule
Course schedule
Duration: July 2026 - June 2027
Timing: Friday & Saturday: 4 pm -8pm ; Sunday:10am-1 pm/2 pm-5 pm
Fee structure
Fee structure
Course Fees: INR 75,000/- (Rs. Seventy-five thousand only) inclusive of GST
Admission
Admission
Important Dates (Tentative)
Application start date: 03rd May 2026
Deadline for applications: 15th June 2026
Interview Sessions: 30th June to 05th July 2026 (Tentative)
Orientation session: First/Second Week of July 20256 ((Tentative)
Admission Procedure
The online application is followed by an one-on-one interview
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