Programme Parameters
Advanced Postgrad
4 Weeks (40 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
The Introduction to RNA-Seq Analysis course is a free, beginner-friendly self-paced program designed to introduce learners to the basics of RNA sequencing (RNA-Seq) and transcriptomics data analysis. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
The Introduction to RNA-Seq Analysis course is a free, beginner-friendly self-paced program designed to introduce learners to the basics of RNA sequencing (RNA-Seq) and transcriptomics data analysis.
📋 Course Objectives
1. Translate Artificial Intelligence theory into practical, reproducible analysis.
2. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence
🚀 Key Learning Outcomes
• A demonstrable Artificial Intelligence project for your research or industry portfolio.
• 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
Introduction to RNA-Seq and Transcriptomics
What is RNA-Seq? • Basics of RNA and Gene Expression • Introduction to Transcriptomics • Applications of RNA-Seq in Research and Healthcare
Understanding RNA-Seq Data
Types of RNA-Seq Data • Sequencing Reads and Expression Data • Introduction to Gene Expression Profiles • Importance of Data Quality in RNA-Seq Studies
Basics of RNA-Seq Analysis
Introduction to Differential Gene Expression • Understanding Upregulated and Downregulated Genes • Basic Workflow of RNA-Seq Analysis • Simple Data Interpretation Concepts
Visualization and Biological Interpretation
Heatmaps and Expression Visualization Basics • Understanding Expression Patterns • Connecting Gene Expression to Disease and Cellular Functions • Functional Interpretation Concepts
Future Scope and Learning Path
RNA-Seq in Precision Medicine • AI and Data Science in Transcriptomics • Career Opportunities in Bioinformatics and Genomics • Mini Learning Activity / Concept-Based Practice
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | RNA-Seq |
| Covered Tool / Platform | Transcriptomics |
| Covered Tool / Platform | Gene Expression Analysis |
| Covered Tool / Platform | RNA Analysis |
| Covered Tool / Platform | Biological Data Interpretation |
Frequently Asked Questions
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