Master Fundamentals of Computational Biology in 4 weeks through hands-on, project-based online training with DSTC.
The Fundamentals of Computational Biology course is a free, beginner-friendly self-paced program designed to introduce learners to how computational methods are used to study biological systems and life science data. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
The Fundamentals of Computational Biology course is a free, beginner-friendly self-paced program designed to introduce learners to how computational methods are used to study biological systems and life science data.
1. Apply Artificial Intelligence methods to authentic research and industry problems.
2. Produce a reproducible, portfolio-ready project you can cite in a thesis, paper, or job application.
β’ Master's and senior undergraduate students specializing in Artificial Intelligence
β’ R&D engineers and working professionals applying Artificial Intelligence in industry
β’ Academics and educators building research or teaching capacity in Artificial Intelligence
β’ A portfolio-grade Artificial Intelligence deliverable you can defend and extend.
β’ A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
What is Computational Biology? β’ Role of Computing in Biological Research β’ Computational Biology vs Bioinformatics β’ Applications in Healthcare and Biotechnology
DNA, RNA, Proteins, and Genes β’ Introduction to Biological Sequences β’ Genomics and Proteomics Basics β’ Importance of Biological Databases
Sequence Analysis Concepts β’ Pattern Recognition in Biological Data β’ Basic Modeling and Data Interpretation β’ Introduction to Biological Algorithms
Disease and Genetic Research β’ Drug Discovery and Personalized Medicine β’ Agricultural and Biotechnology Applications β’ Computational Biology in Scientific Research
AI and Data Science in Computational Biology β’ Emerging Trends in Life Science Research β’ Career Opportunities in Computational Biology β’ Mini Learning Activity / Concept-Based Practice
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Computational Biology |
| Covered Tool / Platform | Biological Data |
| Covered Tool / Platform | Sequence Analysis |
| Covered Tool / Platform | Genomics |
| Covered Tool / Platform | Proteomics |
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