Programme Parameters
Advanced Postgrad
3 Days (4.5 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Bioprocess engineering and fermentation are central to pharmaceuticals, biofuels, food technology, and enzyme production. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
Bioprocess engineering and fermentation are central to pharmaceuticals, biofuels, food technology, and enzyme production.
📋 Course Objectives
1. Apply bioinformatics methods to authentic research and industry problems.
2. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in bioinformatics
• R&D engineers and working professionals applying bioinformatics in industry
• Academics and educators building research or teaching capacity in bioinformatics
🚀 Key Learning Outcomes
• A portfolio-grade bioinformatics deliverable you can defend and extend.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Day 1 – Foundations of AMR, HGT & Bioinformatics Tools
Explore global burden and clinical significance of Antimicrobial Resistance • Identify mechanisms of resistance and key pathogenic species • Examine Horizontal Gene Transfer pathways and mobile genetic elements • Navigate NCBI GenBank, CARD, BLAST, and annotation pipelines
Day 2 – Advanced Bioinformatics & Systems Integration
Perform genomic and metagenomic analyses for AMR surveillance • Construct whole‑genome sequencing (WGS) workflows • Apply network biology and phylogenetics to track gene flow • Build predictive models of resistance spread
Day 3 – Bioreactor Design & Optimization Using Digital Twins
Model microbial growth kinetics and key fermentation parameters • Create digital‑twin based bioreactor simulations • Integrate real‑time AMR data into process control loops • Apply AI/ML algorithms for predictive control and anomaly detection
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | NCBI GenBank |
| Covered Tool / Platform | CARD |
| Covered Tool / Platform | BLAST |
| Covered Tool / Platform | Genome Annotation Pipelines |
| Covered Tool / Platform | Python |
| Covered Tool / Platform | TensorFlow |
| Covered Tool / Platform | Scikit-learn |
| Covered Tool / Platform | MATLAB/Simulink |
| Covered Tool / Platform | AnyLogic |
Programme Faculty & Mentors
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