| Attribute | Detail |
|---|---|
| Format | Online, self-paced course |
| Level | Basic / Beginner |
| Duration | 2–3 Weeks |
| Certification | e-Certification |
| Fee | ₹199 / $20 |
| Tools | Artificial Intelligence Genomics DNA Analysis Machine Learning Basics Genetic Data Interpretation |
About the AI in Genomics: Basics Course
The AI in Genomics: Basics course is a free, beginner-friendly self-paced program designed to introduce learners to how artificial intelligence is used in genomics and genetic research.
The course explains how AI helps researchers analyze genomic data, identify patterns in DNA sequences, study genetic variations, and support healthcare innovation. Learners will explore basic concepts of genomics, machine learning, gene analysis, and AI-driven applications in personalized medicine and biotechnology.
Program Highlights
• Free beginner-level AI in genomics course
• Online self-paced learning format
• Simple explanation of AI and genomic data concepts
• Covers DNA analysis, gene patterns, and predictive applications
• Real-world examples from healthcare and biotechnology
• Suitable for students and non-technical learners
• e-Certification upon successful completion
Course Curriculum
Module 1: Introduction to AI and Genomics
- What is Artificial Intelligence?
- Basics of Genomics and DNA
- Role of AI in Genomic Research
- Applications in Healthcare and Biotechnology
Module 2: Understanding Genomic Data
- DNA, Genes, and Genetic Variations
- Introduction to Sequencing Data
- Gene Expression and Biological Information
- Importance of Data Quality in Genomics
Module 3: AI Concepts in Genomics
- Introduction to Machine Learning Basics
- Pattern Recognition in Genomic Data
- AI for Variant and Disease Prediction
- Basic Predictive Analysis Concepts
Module 4: Applications of AI in Genomics
- AI in Disease Research and Diagnostics
- Personalized Medicine and Precision Healthcare
- Drug Discovery and Biomarker Identification
- Genomics in Biotechnology and Agriculture
Module 5: Future Scope and Learning Path
- Emerging Trends in AI-Driven Genomics
- Big Data and Cloud Genomics Concepts
- Career Opportunities in AI and Genomics
- Mini Learning Activity / Concept-Based Practice
Tools, Techniques, or Platforms Covered
Artificial Intelligence Genomics DNA Analysis Machine Learning Basics Genetic Data Interpretation
Real-World Applications
- Analyzing genetic variations and DNA patterns
- Supporting personalized healthcare and precision medicine
- Identifying disease-related genomic markers
- Improving biotechnology and drug discovery research
- Preparing for advanced learning in bioinformatics and genomic AI
Who Should Attend & Prerequisites
- This course is suitable for students, beginners, healthcare learners, biotechnology learners, bioinformatics learners, and researchers interested in AI and genomics.
- It is also useful for learners from biotechnology, genetics, medicine, pharmacy, biomedical science, bioinformatics, and data science backgrounds.
Certification
