Professional Certification in Machine Learning & AI for Biotechnology and Bioinformatics

This course introduces core machine learning and AI concepts through the lens of biological problem-solving — from feature representation of biological sequences to model evaluation on genomics and biomedical datasets. Learners work through real-world-style case studies spanning genomics, drug discovery, and systems biology, building the judgment to choose appropriate models and interpret their outputs responsibly rather than treating AI as a black box.

Duration

3 Months

Mode

Online

Eligibility

Recommended for students and professionals in bioinformatics, computational biology, or data science who want to apply machine learning specifically to biological problems. Basic Python literacy is helpful; core ML concepts are taught from the ground up.

Certification

LISAINEX Certificate of Completion

Highlights

Theory paired with real coding practice
Genomics, drug discovery, and systems biology case studies
Emphasis on responsible model evaluation

Course Modules / Syllabus

1Machine learning fundamentals for biological data
2Feature engineering for sequence and omics data
3Applications in genomics and variant interpretation
4AI approaches in drug discovery and biomedical informatics
5Model evaluation, validation, and pitfalls in biological ML
6Applied case-study project

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