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DSTC-A66 Online (e-LMS) Advanced Postgrad

Genetic Data Analysis: Introduction

by - DSTC

Master Genetic Data Analysis: Introduction in 4 weeks through hands-on, project-based online training with DSTC.

★★★★★ Be the first to review • 4 Weeks · 40 hrs • e-Certificate Included
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From ₹200 + GST

Programme Parameters

Educational Level:
Advanced Postgrad
Duration & Workload:
4 Weeks (40 Hrs)
Delivery Mode:
Online (e-LMS)
Prerequisites:
• 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 Genetic Data Analysis: Introduction course is a free, beginner-friendly self-paced program designed to introduce learners to the fundamental concepts and methods used in genetic data analysis. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.

🎯 Program Aim

The Genetic Data Analysis: Introduction course is a free, beginner-friendly self-paced program designed to introduce learners to the fundamental concepts and methods used in genetic data analysis.

📋 Course Objectives

1. Put Artificial Intelligence techniques to work on real datasets and case studies.
2. Build a defensible project you can showcase to supervisors, reviewers, or employers.

👥 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 portfolio-grade Artificial Intelligence deliverable you can defend and extend.
• 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 recordings
🎓

e-Certificate on Completion

Cryptographically verified credential
💬

Post-Programme Support

Direct access to mentors & council
💻

Hands-On Experience

Notebooks, real-world code & datasets

Curriculum Outline

Module 1 Outline

Introduction to Genetic Data

What is Genetic Data? • Overview of DNA, RNA, and Protein Sequences • The Role of Genetics in Biology and Medicine • Applications of Genetic Data Analysis

Module 2 Outline

Types of Genetic Data

Genomic Data vs Transcriptomic Data • DNA Sequencing and Gene Expression Data • Genetic Variants and Mutations • Genetic Databases and Tools

Module 3 Outline

Genetic Data Processing and Cleaning

Introduction to Raw Genetic Data (FASTQ, BAM, VCF) • Data Quality Control and Filtering • Basic Data Preparation for Analysis • Exploring Genomic Datasets

Module 4 Outline

Basic Genetic Data Analysis Techniques

Identifying Genetic Variants (SNPs, InDels) • Gene Expression Analysis • Introduction to Association Studies (GWAS) • Basic Statistical Methods in Genetic Analysis

Module 5 Outline

Applications of Genetic Data Analysis

Genetic Disease Research • Personalized Medicine and Pharmacogenomics • Biotechnology and Agricultural Applications • Genetic Data in Public Health and Epidemiology

Technical Specifications

ParameterRequirement
Covered Tool / PlatformGenetic Data
Covered Tool / PlatformDNA Sequencing
Covered Tool / PlatformGene Expression
Covered Tool / PlatformGenomic Data Processing
Covered Tool / PlatformStatistical Analysis for Genetics

Frequently Asked Questions

Yes. This is a free online self-paced course designed for beginners.

No. The course focuses on understanding genetic data analysis concepts and does not require coding experience.

You will learn the basics of genetic data analysis, including DNA sequencing, gene expression, genetic variation, and data processing techniques.

Students, beginners, researchers, and professionals from any background interested in genetics and data analysis can join.

Yes. Learners receive an e-Certification after completing the course.

Genetic data analysis involves processing and analyzing genetic information, such as DNA sequences and gene expression, to uncover insights related to biological functions, diseases, and traits.

No, a background in genetics is not required. The course is designed to introduce genetic data analysis to beginners with basic knowledge of biology helpful, but not mandatory.

After completing the course, learners can pursue roles in genomics, bioinformatics, biotechnology research, and related fields, particularly in genetic data analysis and genetic epidemiology. The Genetic Data Analysis: Introduction course provides a simple and structured foundation in understanding and analyzing genetic data. It is an ideal starting point for learners interested in genomics, bioinformatics, disease research, and data-driven biological studies.

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