| Attribute | Detail |
|---|---|
| Format | Online, self-paced course |
| Level | Beginner |
| Duration | 2–3 Weeks |
| Certification | e-Certification |
| Fee | ₹199 / $20 |
| Tools | Single-Cell Genomics Single-Cell RNA Sequencing Gene Expression Analysis Data Visualization Bioinformatics Tools for Single-Cell Analysis |
About the Introduction to Single-Cell Genomics Course
The Introduction to Single-Cell Genomics course is a free, beginner-friendly self-paced program designed to introduce learners to the cutting-edge field of single-cell genomics and its applications in modern biological research.
The course explains how single-cell genomics allows researchers to analyze individual cells, providing a deeper understanding of cellular diversity, gene expression, and molecular mechanisms. Learners will explore concepts such as single-cell RNA sequencing (scRNA-seq), data analysis, and the role of single-cell technologies in disease research, development, and personalized medicine.
Program Highlights
• Free beginner-level single-cell genomics course
• Online self-paced learning format
• Simple explanation of single-cell genomics concepts
• Covers techniques, data analysis, and real-world applications
• Real-world examples from genomics, healthcare, and biotechnology
• Suitable for students and non-technical learners
• e-Certification upon successful completion
Course Curriculum
Module 1: Introduction to Single-Cell Genomics
- What is Single-Cell Genomics?
- Why Study Single Cells?
- Overview of Single-Cell Technologies
- Applications of Single-Cell Genomics in Modern Research
Module 2: Single-Cell RNA Sequencing (scRNA-seq)
- What is scRNA-seq?
- Basic Workflow of Single-Cell RNA Sequencing
- Understanding Gene Expression at the Single-Cell Level
- Key Technologies for Single-Cell RNA Analysis
Module 3: Single-Cell Genomic Data
- Handling Single-Cell Genomic Data
- Data Formats and Storage (FASTQ, BAM, H5)
- Basic Data Quality Control and Filtering
- Challenges in Single-Cell Data Analysis
Module 4: Analyzing Single-Cell Data
- Clustering Single-Cell Data
- Identifying Cell Types and States
- Data Integration and Normalization Techniques
- Basic Visualization of Single-Cell Data
Module 5: Applications and Future Scope
- Single-Cell Genomics in Disease Research
- Applications in Cancer, Immunology, and Neuroscience
- Single-Cell Genomics in Drug Discovery and Personalized Medicine
- Emerging Trends and Future of Single-Cell Technologies
Tools, Techniques, or Platforms Covered
Single-Cell Genomics Single-Cell RNA Sequencing Gene Expression Analysis Data Visualization Bioinformatics Tools for Single-Cell Analysis
Real-World Applications
- Studying gene expression at the individual cell level
- Identifying cellular heterogeneity in diseases like cancer
- Personalized medicine and precision therapeutics
- Exploring the immune system and neuroscience at the single-cell scale
- Supporting drug discovery with single-cell data insights
Who Should Attend & Prerequisites
- This course is suitable for students, beginners, researchers, and professionals interested in single-cell genomics, molecular biology, and modern biological research.
- It is also useful for learners from bioinformatics, biotechnology, genomics, life sciences, medicine, and healthcare backgrounds.
Certification
