Programme Parameters
Graduate / Intermediate
3 Days (4.5 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Microbiology has entered a new era where petri-dish observations alone are no longer sufficient to keep up with the scale of biological data. From imaging colony growth to sequencing microbial communities, researchers now face an influx of complex data requiring advanced analysis. This course explores how AI techniques such as machine learning, computer vision, and predictive analytics are revolutionizing microbiology. Across 4 Weeks, you will go deep on machine learning and computer vision, then consolidate everything in a capstone project. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
Microbiology has entered a new era where petri-dish observations alone are no longer sufficient to keep up with the scale of biological data. From imaging colony growth to sequencing microbial communities, researchers now face an influx of complex data requiring advanced analysis. This course explores how AI techniques such as machine learning, computer vision, and predictive analytics are revolutionizing microbiology.
📋 Course Objectives
1. Get comfortable working with machine learning.
2. Build practical fluency in computer vision.
3. Translate biotechnology theory into practical, reproducible analysis.
4. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in biotechnology
• R&D engineers and working professionals applying biotechnology in industry
• Academics and educators building research or teaching capacity in biotechnology
• Data and computational scientists moving into machine learning
🚀 Key Learning Outcomes
• Confidence to reason about machine learning in real projects.
• Confidence to apply computer vision in real projects.
• A portfolio-grade biotechnology 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
Automating What the Plate Shows
• Colony counting and morphology quantification from plate images
• Segmentation of touching and overlapping colonies as the hard case
• Illumination, plate reflection and the imaging setup that decides accuracy
Classifying Organisms
• MALDI-TOF spectra and library-based identification with its coverage gaps
• Machine learning on microscopy images for morphology-based classification
• Sequence-based identification and where phenotype and genotype disagree
Predicting Susceptibility
• Genotypic AST prediction against phenotypic testing, and current accuracy
• Species-dependent performance and the resistance mechanisms models miss
• Clinical breakpoints, EUCAST and CLSI, and why prediction must be conservative
Learning from Sequence Data
• Amplicon and shotgun data reduced to features for machine learning
• Compositionality — relative abundance data breaks standard statistics
• Classifier performance on microbiome data and the overfitting that is endemic
Deploying Models in a Laboratory
• Validation against the reference method the laboratory already trusts
• Batch effects between runs, operators and media lots
• Regulatory position for diagnostic use and the limits of research-use claims
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | TensorFlow |
| Covered Tool / Platform | PyTorch |
| Covered Tool / Platform | Keras |
| Covered Tool / Platform | Scikit-learn |
| Covered Tool / Platform | Jupyter Notebook |
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | Hugging Face |
Programme Faculty & Mentors
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