| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Beginner |
| Duration | 4 Weeks |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹199 / $59 |
| Tools | BWA SAMtools GATK FastQC Trimmomatic R/Bioconductor IGV PLINK |
About the AI in Genomics & Personalized Medicine Course
AI in Genomics & Personalized Medicine is a comprehensive beginner-level program offered by NanoSchool (NSTC) that provides in-depth training in AI in Genomics. The course covers critical areas including Personalized Medicine, equipping learners with both theoretical foundations and practical expertise. Through a carefully structured curriculum, participants will develop the skills needed to tackle real-world challenges in Genomics.
Whether you are a student looking to enter the field of Genomics, a working professional seeking to upgrade your skill set, or a researcher exploring new methodologies, this course offers a structured learning pathway. Each module combines theoretical concepts with hands-on exercises, case studies, and projects to ensure practical mastery. Upon completion, learners will earn an e-Certification and e-Marksheet from NSTC.
Program Highlights
• Comprehensive coverage of AI in Genomics from fundamentals to advanced applications
• Hands-on projects and real-world case studies in Genomics
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Exposure to industry-standard tools and platforms used in Genomics
• Career-oriented training for academic and professional growth in Genomics
Course Curriculum
Module 1: Introduction to AI in Genomics
- Overview and historical evolution of AI in Genomics
- Key terminology, definitions, and core concepts in Genomics
- Current industry landscape, trends, and career opportunities
- Setting up the learning environment and essential tools
Module 2: Fundamentals and Theoretical Foundations
- Core principles and scientific/theoretical underpinnings of AI in Genomics
- Mathematical and analytical frameworks relevant to Genomics
- Comparative analysis of major approaches and methodologies
- Understanding key standards, guidelines, and best practices
Module 3: Personalized Medicine
- Core concepts and techniques in Personalized Medicine
- Practical implementation and hands-on exercises
- Integration of Personalized Medicine with AI in Genomics workflows
- Case study: Real-world application of Personalized Medicine
Module 4: NGS Data Analysis
- Introduction to NGS Data Analysis concepts and methodologies
- Step-by-step practical implementation of NGS Data Analysis techniques
- Tools and platforms commonly used for NGS Data Analysis
- Troubleshooting, optimization, and best practices
Module 5: Variant Calling
- Introduction to Variant Calling concepts and methodologies
- Step-by-step practical implementation of Variant Calling techniques
- Tools and platforms commonly used for Variant Calling
- Troubleshooting, optimization, and best practices
Module 6: Advanced Topics and Emerging Trends in Genomics
- Cutting-edge research and innovations in AI in Genomics
- Integration with AI, automation, and modern technologies
- Industry case studies and real-world problem solving
- Future directions and career pathways in Genomics
Module 7: Capstone Project and Assessment
- End-to-end project implementation using AI in Genomics skills
- Peer review, collaborative exercises, and expert feedback
- Portfolio-ready project documentation and presentation
- Final assessment and course completion evaluation
Tools, Techniques, or Platforms Covered
BWA SAMtools GATK FastQC Trimmomatic R/Bioconductor IGV PLINK
Real-World Applications
- Apply AI in Genomics skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical Genomics competencies
- Solve industry-relevant problems using AI in Genomics methodologies and tools
- Contribute to open-source projects and collaborative research in Genomics
- Prepare for competitive examinations, interviews, and professional certifications in Genomics
Who Should Attend & Prerequisites
- Students pursuing degrees in Genomics, science, engineering, or related disciplines
- Working professionals seeking to upskill or transition into Genomics roles
- Researchers and academicians looking to adopt modern techniques in Genomics
- Entrepreneurs, freelancers, and self-learners interested in practical Genomics knowledge
Certification
