Bioinformatics Analyst : LSSSDC (Govt. of India) Certified Course

A comprehensive 6-month government-certified course providing advanced bioinformatics training with 28 credits, third-party examination, 100% job placement assistance, and research publication guidance.

Course Live Advanced LSSSDC

Language English

Level Advanced

Updated Feb 2026

Bioinformatics Analyst : LSSSDC (Govt. of India) Certified Course

Course Description

This is a Super 30 Bioinformatics Batch offering a 6-month comprehensive training program certified by LSSSDC (Life Sciences Sector Skill Development Council), Government of India. The course provides 28 credits, includes third-party examination, and offers 100% job placement assistance with exclusive interview opportunities. Participants receive research guidance and publication support, hands-on training with a practical approach, and live interaction with industry experts.

What You'll Learn

Practical Bioinformatics Skills: Hands-on experience in bioinformatics tools and techniques for real-world applications

Sequence Analysis Proficiency: Techniques for sequence alignment, genomics, and proteomics using BLAST and ClustalW

Data Management and Retrieval: Navigating, importing, and managing data from bioinformatics databases (GenBank, PDB, UCSC)

Programming Skills: Proficiency in Python, R, and Linux for bioinformatics applications

Algorithm and Data Structure Knowledge: Essential algorithms and data structures for bioinformatics

Machine Learning and AI: Applying ML techniques to bioinformatics data analysis

Research Publication Guidance: Conducting research and publishing findings in reputable journals

Career Readiness: 100% placement assistance with career counseling and interview preparation

Industry Certification: Government-recognized certificate validating bioinformatics proficiency

Networking Opportunities: Connecting with industry professionals and staying updated on bioinformatics trends

Curriculum

Introduction to Bioinformatics and its Applications in Life Sciences (1 Hour)
Lesson
Types of sequencing and NGS introduction (1 Hour)
Lesson
Introduction to NGS applications (1 Hour)
Lesson

NCBI overview (1 Hour)
Lesson
NCBI Gene database (1 Hour)
Lesson
UCSC Genome Browser Overview (1 Hour)
Lesson
UCSC Genome Browser Hands-on Exercises (1 Hour)
Lesson
Pubmed Database Introduction (1 Hour)
Lesson
Clinvar Database Overview (1 Hour)
Lesson
KEGG Database Overview and Exercises (1 Hour)
Lesson
Protein Databases (UniProt) (1 Hour)
Lesson
Protein Databases (PDB) (1 Hour)
Lesson
Ensemble Database (1 Hour)
Lesson

Online BLAST Introduction and Exercises (1 Hour)
Lesson
Setting Up Standalone BLAST and Hands-on Exercises (1 Hour)
Lesson
Advanced Standalone BLAST Applications and Exercises (1 Hour)
Lesson
Primer Design Using Primer3 / NCBI Primer-BLAST (1 Hour)
Lesson
Multiple Sequence Alignment Using MEGA (1 Hour)
Lesson

Introduction to Linux: Overview and Installation (1 Hour)
Lesson
Essential Linux Commands for Beginners (1 Hour)
Lesson
Advanced Linux Commands (1 Hour)
Lesson
Package Management using Repository (1 Hour)
Lesson
Bash Scripting, AWK and SED (1 Hour)
Lesson

Introduction to Python (1 Hour)
Lesson
Data Types (1 Hour)
Lesson
String Handling (1 Hour)
Lesson
Data Structure (1 Hour)
Lesson
Control Structure (1 Hour)
Lesson
Function (1 Hour)
Lesson
File Handling (1 Hour)
Lesson
Data Manipulation (1 Hour)
Lesson
Biopython (1 Hour)
Lesson

Introduction and Installation of R (1 Hour)
Lesson
Data Types in R (1 Hour)
Lesson
Data Structure (1 Hour)
Lesson
File Handling (1 Hour)
Lesson
Control Structure (1 Hour)
Lesson
Function (1 Hour)
Lesson
Package Management (1 Hour)
Lesson
Data Manipulation (1 Hour)
Lesson
Data Visualization (1 Hour)
Lesson
Statistical Analysis (1 Hour)
Lesson

Basic Terminologies in NGS (1 Hour)
Lesson
Understanding of SRA database (1 Hour)
Lesson
Tools installation in Linux for Variation Calling (1 Hour)
Lesson
Quality control (1 Hour)
Lesson
Trimming of Reads (1 Hour)
Lesson
Indexing of Genome and Alignment of Reads (1 Hour)
Lesson
Variation calling using GATK (1 Hour)
Lesson
Variant Effect Prediction (1 Hour)
Lesson
Variation Visualization (1 Hour)
Lesson

Introduction to Cancer Genomics and Data Retrieval (1 Hour)
Lesson
Genomic Profiling and Mutation Analysis (1 Hour)
Lesson
The Cancer Genome Atlas (TCGA) (1 Hour)
Lesson
Biomarkers and Targeted Cancer Therapies (1 Hour)
Lesson
Functional Genomics in Cancer Research (1 Hour)
Lesson

Introduction to RNAseq and it's basic terminologies (1 Hour)
Lesson
Tools installation in Linux for Gene Expression analysis (1 Hour)
Lesson
Quality control and Trimming of reads (1 Hour)
Lesson
Indexing of Genome and Alignment of Reads (1 Hour)
Lesson
Normalization of Data (Cufflinks) (1 Hour)
Lesson
Merging of Data and Differential expression of genes (1 Hour)
Lesson
Understanding of DEG results (1 Hour)
Lesson
Annotation of DEG (1 Hour)
Lesson
Functional and Pathway Enrichment Analysis (1 Hour)
Lesson
Network Analysis (1 Hour)
Lesson

Tools installation for De-novo RNAseq (1 Hour)
Lesson
Data downlading and Quality control (1 Hour)
Lesson
Assembly Creation (1 Hour)
Lesson
Abundance count estimation (1 Hour)
Lesson
Generation of count matrix and DEG (1 Hour)
Lesson
BLAST (1 Hour)
Lesson
Understanding the DEG results (1 Hour)
Lesson
Annotation of DEGs (1 Hour)
Lesson
Encrichment Analysis (1 Hour)
Lesson

Introduction to metagenomics (1 Hour)
Lesson
Tools installation for metagenomics (1 Hour)
Lesson
Data Downloading (1 Hour)
Lesson
Quality control & Trimming (1 Hour)
Lesson
Data importing in Qimme2 (1 Hour)
Lesson
Data quality check using DADA2 (1 Hour)
Lesson
Phylogentic Analysis (1 Hour)
Lesson
Taxonomy Analysis (1 Hour)
Lesson
Krona Plot (1 Hour)
Lesson
Phylogenetic tree construction (1 Hour)
Lesson

Introduction to Microarray (1 Hour)
Lesson
Data Downloading (1 Hour)
Lesson
Microarray Pipeline upto Normalization (1 Hour)
Lesson
Microarray Pipeline till DEG (1 Hour)
Lesson
Annotation of DEG (1 Hour)
Lesson
Encrichment Analysis (1 Hour)
Lesson
Network Analysis (1 Hour)
Lesson
Volcano Plot (1 Hour)
Lesson
Heatmap (1 Hour)
Lesson

Machine Learning Fundamentals for Bioinformatics (1 Hour)
Lesson
Linear Models and Nearest Neighbors (1 Hour)
Lesson
Basics of Probabilistic Machine Learning (1 Hour)
Lesson
Implementing Support Vector Machines (SVM) (1 Hour)
Lesson
Introduction to Naive Bayes Classifier (1 Hour)
Lesson
Decision Tree and Random Forest Classifier (1 Hour)
Lesson
Logistic Regression in Bioinformatics (1 Hour)
Lesson
Introduction to Clustering Algorithms (1 Hour)
Lesson
Validation of Machine Learning Models (1 Hour)
Lesson
Machine Learning for Image Analysis (1 Hour)
Lesson

Introduction to Statistical Methods for Data Extraction and Preparation in Bioinformatics (1 Hour)
Lesson
Exploring Data Characteristics and Distribution: Descriptive Statistics and Data Structures (1 Hour)
Lesson
Understanding Correlation and Regression Analysis in Bioinformatics (1 Hour)
Lesson
Probability and Bayes Theorem: Foundations for Statistical Inference (1 Hour)
Lesson
Sampling Techniques and Distribution Theory in Bioinformatics (1 Hour)
Lesson
Hypothesis Testing: Concepts and Methods for Data Analysis (1 Hour)
Lesson
Statistical Tools for Data Management, Analysis, and Visualization in Bioinformatics (1 Hour)
Lesson
Inferential Statistics: Making Valid Generalizations from Sample Data (1 Hour)
Lesson
Interpreting Statistical Outputs for Informed Decision Making in Bioinformatics (1 Hour)
Lesson
Practical Applications: Applying Statistical Methods to Solve Bioinformatics Problems (1 Hour)
Lesson

Program Design: Principles and Methods (1 Hour)
Lesson
Basic Structures for Algorithm Development (1 Hour)
Lesson
Efficient vs Naïve Algorithms (1 Hour)
Lesson
Structured Programming and Divide and Conquer (1 Hour)
Lesson
Object -Oriented Approaches and Greedy Algorithms (1 Hour)
Lesson

Introduction to AWS (1 Hour)
Lesson
Introduction to Compute Storage Databases (1 Hour)
Lesson
Introduction to AWS Services Networking Security (1 Hour)
Lesson
Deployment Strategies on AWS (1 Hour)
Lesson
Management Tools for Bioinformatics Workflows on AWS (1 Hour)
Lesson

Introduction to SQL (Structured Query Language) for Bioinformatics (1 Hour)
Lesson
Basic SQL Syntax and Data Types: Queries, Statements, and Operators (1 Hour)
Lesson
Relational Databases: INSERT, UPDATE, and DELETE (1 Hour)
Lesson
Aggregating Data: Using GROUP BY and Aggregate (1 Hour)
Lesson
Data Import, Export, and Manipulation in SQL (1 Hour)
Lesson

Drug Discovery and Development Process: Understanding QSAR Principles (1 Hour)
Lesson
Introduction to Drug Discovery Process (1 Hour)
Lesson
Role of Computational Methods (1 Hour)
Lesson
Utilizing Biological Databases and GCP Standards (1 Hour)
Lesson
Chemical Structure Visualization (1 Hour)
Lesson
Visual Representation of Biological Processes and Structures in Data Analysis (1 Hour)
Lesson
Biomolecules- Properties and function (1 Hour)
Lesson
Molecular Docking and Molecular Dynamics (1 Hour)
Lesson
Pharmacophore Modeling (1 Hour)
Lesson
Pharmacophore Modelling applications (1 Hour)
Lesson

Course Fee

₹120000.00

~~₹120000.00~~

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Skills You'll Gain

Bioinformatics Analysis Next-Generation Sequencing (NGS) Python Programming R Programming Linux Command Line Sequence Analysis Variant Calling RNAseq Analysis Microarray Analysis Metagenomics Machine Learning Statistical Analysis Database Management (NCBI PDB) BLAST Algorithm Development Cloud Computing (AWS) SQL Database Management Cheminformatics Molecular Docking Research Publication Scientific Writing Data Visualization

Requirements

Educational: Bachelor's degree in life sciences, biotechnology, bioinformatics, or related field (preferred)
Prerequisites: Basic understanding of biology
Technical: Reliable internet connection, functional computer, necessary software
Attendance: Minimum 75% attendance requirement
Examination: Must clear third-party government exam
Commitment: Ability to complete assignments and projects on time

Who This Course Is For

Life Sciences Graduates (Biotechnology, Microbiology, Biochemistry)
Bioinformatics Students and Professionals
Research Scholars and PhD Candidates
Healthcare Professionals
Data Scientists interested in biological data
Academic Professionals seeking industry certification
Career changers entering bioinformatics field

Bioinformatics Analyst : LSSSDC (Govt. of India) Certified Course

Course Description

What You'll Learn

Curriculum

Introduction to Bioinformatics (3 lectures)

Introduction to Bioinformatics and its Applications in Life Sciences (1 Hour)

Types of sequencing and NGS introduction (1 Hour)

Introduction to NGS applications (1 Hour)

MODULE 2: INTRODUCTION TO BIOINFORMATICS DATABASES (10 Lectures

NCBI overview (1 Hour)

NCBI Gene database (1 Hour)

UCSC Genome Browser Overview (1 Hour)

UCSC Genome Browser Hands-on Exercises (1 Hour)

Pubmed Database Introduction (1 Hour)

Clinvar Database Overview (1 Hour)

KEGG Database Overview and Exercises (1 Hour)

Protein Databases (UniProt) (1 Hour)

Protein Databases (PDB) (1 Hour)

Ensemble Database (1 Hour)

MODULE 3: BIOINFORMATICS TOOLS (5 Lectures)

Online BLAST Introduction and Exercises (1 Hour)

Setting Up Standalone BLAST and Hands-on Exercises (1 Hour)

Advanced Standalone BLAST Applications and Exercises (1 Hour)

Primer Design Using Primer3 / NCBI Primer-BLAST (1 Hour)

Multiple Sequence Alignment Using MEGA (1 Hour)

MODULE 4: Linux for Beginners: A Practical Guide (5 Lectures)

Introduction to Linux: Overview and Installation (1 Hour)

Essential Linux Commands for Beginners (1 Hour)

Advanced Linux Commands (1 Hour)

Package Management using Repository (1 Hour)

Bash Scripting, AWK and SED (1 Hour)

MODULE 5: INTRODUCTION TO PYTHON PROGRAMMING (10 Lectures)

Introduction to Python (1 Hour)

Data Types (1 Hour)

String Handling (1 Hour)

Data Structure (1 Hour)

Control Structure (1 Hour)

Function (1 Hour)

File Handling (1 Hour)

Data Manipulation (1 Hour)

Biopython (1 Hour)

MODULE 6: DATA ANALYSIS WITH R PROGRAMMING (10 Lectures)

Introduction and Installation of R (1 Hour)

Data Types in R (1 Hour)

Data Structure (1 Hour)

File Handling (1 Hour)

Control Structure (1 Hour)

Function (1 Hour)

Package Management (1 Hour)

Data Manipulation (1 Hour)

Data Visualization (1 Hour)

Statistical Analysis (1 Hour)

MODULE 7: VARIENT CALLING ANALYSIS BY DNAseq (9 Lectures)

Basic Terminologies in NGS (1 Hour)

Understanding of SRA database (1 Hour)

Tools installation in Linux for Variation Calling (1 Hour)

Quality control (1 Hour)

Trimming of Reads (1 Hour)

Indexing of Genome and Alignment of Reads (1 Hour)

Variation calling using GATK (1 Hour)

Variant Effect Prediction (1 Hour)

Variation Visualization (1 Hour)

MODULE 8: GENOMIC INSIGHTS FOR CANCER RESEARCH (5 Lectures)

Introduction to Cancer Genomics and Data Retrieval (1 Hour)

Genomic Profiling and Mutation Analysis (1 Hour)

The Cancer Genome Atlas (TCGA) (1 Hour)

Biomarkers and Targeted Cancer Therapies (1 Hour)

Functional Genomics in Cancer Research (1 Hour)

MODULE 9: REFERENCE BASED RNAseq ANALYSIS (10 Lectures)

Introduction to RNAseq and it's basic terminologies (1 Hour)

Tools installation in Linux for Gene Expression analysis (1 Hour)

Quality control and Trimming of reads (1 Hour)

Indexing of Genome and Alignment of Reads (1 Hour)

Normalization of Data (Cufflinks) (1 Hour)

Merging of Data and Differential expression of genes (1 Hour)

Understanding of DEG results (1 Hour)

Annotation of DEG (1 Hour)

Functional and Pathway Enrichment Analysis (1 Hour)

Network Analysis (1 Hour)

MODULE 10: De-novo RNA Seq: Transcriptome Assembly and Analysis (10 Lectures)