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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery	Frequency Of Classes
English	Self Study, Virtual Classroom	Video and Text Based	Weekends

Course Overview

Functional genomics investigations can make use of a variety of methods, ranging from high-throughput technologies such as next-generation sequencing and microarrays to RT-PCR. The Transcriptome Data Analysis online course covers all of the functional elements of transcriptomic data analysis.

The technique chosen by the candidate will be determined by the size and scope of the experiment. When developing the experiment, candidates will consider the benefits and drawbacks of each technology, as well as if they are appropriate for the sort of planned experiment. The Transcriptome Data Analysis training provides both the theoretical and practical processes necessary for experiment preparation and hypothesis testing.

The 26 hours course is jointly provided by Edu Plus Now, in collaboration with the Indian Statistical Institute Pune. The Transcriptome Data Analysis syllabus includes various topics such as data extraction, gene network analysis, raw data, functional analysis, quality control management, python, R, statistics, data analysis, data visualization, etc.

The Highlights

Advisory Board members from Industry & Academia
Separate batches for working professional
Weekend batch
Placement Assistance
Industry-Endorsed Curriculum
Projects spanning
Access to Lecture Recordings
Course provider Edu plus now
Offered by ISI, Pune
26 hours duration
Live interactive session
Domain Experts Faculty

Programme Offerings

assignments
online learning
Practicals
Capstone Projects
Certification
Lecture
live sessions

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	edu plus now

Transcriptome Data Analysis Fees

Jointly certification by Edu Plus Now and Indian Statistical Institute Fee

Rs. 15,000 + GST

Eligibility Criteria

Certification Qualifying Details

After finishing the Transcriptome Data Analysis course successfully, students will get a certificate of completion from the Indian Statistical Institute, Pune via Edu Plus Now.

What you will learn

Analytical skillsMachine learningKnowledge of PythonSQL knowledgeTableau knowledge

After completing the Transcriptome Data Analysis online certification course, candidates will learn about SQL, Functional Analytics, Statistical Analysis, Regression Modelling, Text Mining, Hypothesis Testing, Machine Learning Using R, Predictive Analytics, Python, Deep Learning, Natural Language Processing, Neural Networks, Predictive Modelling, Python Spark, Tableau, Big Data Hadoop, Etc.

Who it is for

Candidates who want to learn about SQL, Statistical Analysis, Functional Analytics, Text Mining, Regression Modelling, Predictive Analytics, Machine Learning Using R, Hypothesis Testing, Python, Deep Learning, Natural Language Processing, Predictive Modelling, Neural Networks, Spark, Hadoop, Tableau, etc can join the course.

Admission Details

To get admission to the Transcriptome Data Analysis program from IIT Madras, follow the steps mentioned below:

Step 1. Open the official course page by going through the link given below. (https://www.eduplusnow.com/course-details/transcriptome-data-analysis)

Step 2. Select your study plan by clicking the Enroll Now button.

Step 3. Fill in the required information and submit.

Step 4. Pay the fee and begin learning at the scheduled time.

The Syllabus

Theoretical modules
Basic concept
Data extraction
Microarray Data analysis
Raw data
- Quality control
- Read Alignment
- Mapping output
- Visualization of mapped reads
DEG analysis
Single-cell RNA seq
Gene network analysis
Variant calling
Function analysis

R
Python
Tophat
STAR
Hisat
Bedtools

Introduction to NGS
Microarray, RNA-seq
Bulk vs Single-cell RNA-seq
R
Statistics

Introduction to Biological databases
GEO and SRA database
Data extraction and management

Microarray data analysis
Microarray data visualization

Introduction to bioinformatics file formats
Quality Control
- Preprocessing of raw reads: quality control (FastQC), adapter clipping, quality trimming
Read Alignment
- Introduction to read mapping (Alignment methods
- Mapping heuristics)
- Tophat
- STAR and Hisat
Mapping Output
- SAM and BAM format
- Manipulating SAM/BAM files
Visualization Of Mapped Reads
- IGV
Deg Analysis
- Gene quantifucation
- DeSEQ
- Data visualization