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India's first Industry focused PG program in Bioinformatics

An industry-driven intensive 1-year PG program in collaboration with leading universities, Metaverse campus-Led Learning with Offline Community Experiences

Next Cohort

1st July, 2024

Program Duration

12 Months, Hybrid (25-30 hours/week)

Learn from experts working at

Download Syllabus

Industry PGP in Bioinformatics, Genomics & data science

Join the league of the top 10%

Biotechnologists

"Join the elite league of the top 10% in the field of biotechnology and unlock endless career possibilities with our specialized training, industry connections, and personalized guidance."

Check out our Bversity alumni

Srirathi R

Toxicologist

Sneha Nair

TCS Life science

Chandana

Immunogenix

Sudhanva

USA

Sarvesh

Stanford Online

Harish Krrishna

NE University, USA

Vishwa M

Azooka Life Science

Take the First Step towards becoming a part of the Top 1% of Biotechnologists in the country!

*Admissions Ongoing for 2024

Apply now

Breaking Barriers with Democratised Education

Access high-quality education at 1/10th the price of typical Master's courses.

Tap into the

wisdom of industry experts from the Biotechnology industry

Success Managers

Daily 1:1 Counselling for student’s growth and potential maximisation.

Learning sessions & projects are built by experts in the Biotech industry

Keerthanaasri J P

Ex

BUILT

Healthtech apps

Linkedin

Diksha Pandey

BUILT

100+ workflow pipelines

Linkedin

Ex

Vinay Kumar

LEAD

Product manager

Linkedin

Ex

Berty Ashley

BUILT

Cure for DMD

Linkedin

Gnaneshwar Yadav

BUILT

mRNA translations

Linkedin

Manisha Bhardwaj

BUILT

Proteomics app

Linkedin

Supported & Mentored by India's Top Leaders

Suresh Sambandam

CEO, Kissflow

Convenor, Dream TN

Sathish Kumar

Founder, Milky Mist

Nagaraja Prakasam

Investor, Global mentor

Andi Giri

CEO, Softsquare

and 15+ top leaders

and 30+ Industry Leaders

Excited Already? Download our

brochure and begin your journey!

Download here

Build a portfolio for yourself. Let the industries know the projects you have worked and skillsets you have.

Apply here

1

Work on real-time industry projects

Qualify for jobs at top product startups

2

Stand out to recruiters

Globally-competitive salary based on

your skills.

3

Stand out to recruiters

Get interviews on your calendar directly.

Harish Krishna N

Bioinformatics analyst

Significant experience working with diverse NGS datasets and developing analytical pipelines that can transform genomic data into clinical information thus contributing to improving patient lives.

Tools I am experienced with

Application

Process & Timeline

Step 1

Online Application

Submit the online application along with the required documents.

Step 2

SOP Evaluation

Shortlisted candidates will be required to submit a SOP & attend an assesment.

Step 3

1: 1 Interview

Shortlisted candidates will be called for an online interview. The selected candidates will receive an offer of admission to the programme.

Eligibility

  • B.Tech, B.Sc (4 years) M.Sc & M.Tech Life science/Biotechnology graduates who passed with min 7 CGPA

  • Students with qualifying marks in any entrance ( (CSIR-UGC NET, GAT-B, DBT-JRF, CSIR, ICMR) doesn’t require Assessment Test

Empowering next-gen Biotechnologists

Over 8,000 students have upskilled with Bversity and have started their career with Bversity

Why this is the best for your career ?

1 year of accelerated PG programme

Work on 3+ industry capstone projects

Build your portfolio in the Biotech industry with experts

Learn 15+ tools used in the Biotechnology industry

Industry experts as your mentors

Work in a biotech industry while you learn in your final term

Book your seat with

20,000

Only

Total Program Fee

1,50,000

Next Cohort

1st July, 2024

Program Duration

12 Months, Hybrid (25-30 hours/week)

Get a discount of INR 50,000

Total Course Fee

INR 2,00,000

INR 1,50,000

The discount is valid only for the first few cohort of students joining the batches

Learn With Easy installments & EMI Plans.

The credit facility is provided by a third party credit facility

provider and any arrangement with such third party is

outside Novatr’s purview.

Talk to us today

A carefully crafted curriculum that unlocks advanced career roles for you

Term 1

4 months

1

A carefully crafted learning journey that unlocks advanced career roles for you

  • Understand the key concepts in modern biology and their application to bioinformatics

  • Explore the tools, databases, and resources used in bioinformatics research, and gain proficiency in their usage

  • Develop an understanding of genomics and next-generation sequencing techniques, including data analysis and interpretation

Module 1: Fundamentals of Bioinformatics and Modern Biology

  • Demonstrate proficiency in the basic syntax and structure of Python and R programming languages, including working with variables, data types, operators, and expressions

  • Develop the ability to utilise control flow statements and functions effectively in Python and R to create dynamic and efficient code for various programming tasks

  • Master file handling techniques in both Python and R, including reading and writing files, accepting user input, and handling command-line arguments to enhance program flexibility and interactivity

Module 2: Python & R programming languages

  • Understand different types of datasets and data generation methods used in bioinformatics, as well as common public databases in the field

  • Develop proficiency in using industry-standard tools and libraries for processing and analysing biological data

  • Omics Data Analysis - Tools, Outcomes, Use Cases and Applications

Module 3: Data analysis & visualization

  • Demonstrate proficiency in managing and analysing data by utilising different types of biological databases, applying appropriate database management systems, and implementing data security and privacy measures

  • SQL (structured query language) for relational databases. Master the fundamental concepts and principles of SQL, including syntax, data types, data manipulation, and database management.

  • Apply advanced SQL concepts such as joins, subqueries, views, stored procedures, and functions to query and aggregate data from multiple tables, optimise query performance, and solve real-world data-related problems.

Module 4: Data architecture & database management

  • Build a strong foundation in biostatistics by applying key concepts, such as variability, population, sample, central tendency, and variability, in order to analyse and interpret biological data using descriptive statistics techniques.

  • Apply inferential statistics techniques, such as hypothesis testing and confidence interval construction, to make statistical inferences and draw conclusions about populations based on sample data.

  • Design and implement biotechnology experiments using appropriate experimental design principles, including randomization, replication, and blocking, to ensure reliable and valid results.

Module 5: Introduction to Statistics in Biotechnology

  • Explain the fundamental concepts of Artificial Intelligence (AI) and Machine Learning (ML), including their different types and applications.

  • Implement common Machine Learning algorithms (e.g. Linear Regression, Decision Trees) using popular libraries like scikit-learn to analyse biological data and interpret the results.

  • Critically evaluate the strengths and limitations of Deep Learning architectures (e.g., CNNs, RNNs) for specific bioinformatics tasks, considering tools like TensorFlow and PyTorch for implementation.

Module 6: AI & ML in Biotechnology

Download detailed syllabus

Concepts covered

Tools you will use to learn

Brush up your basics & get started

What can you expect ?

720 hours of technical learning

48 hours of soft-skill building

1 capstone industry project

2 weeks of hackathons, workshops & bootcamps with the industry

Term 2

4 months

1

A carefully crafted learning journey that unlocks advanced career roles for you

  • Understand the key concepts in modern biology and their application to bioinformatics

  • Explore the tools, databases, and resources used in bioinformatics research, and gain proficiency in their usage

  • Develop an understanding of genomics and next-generation sequencing techniques, including data analysis and interpretation

Module 1: Fundamentals of Bioinformatics and Modern Biology

  • Demonstrate proficiency in the basic syntax and structure of Python and R programming languages, including working with variables, data types, operators, and expressions

  • Develop the ability to utilise control flow statements and functions effectively in Python and R to create dynamic and efficient code for various programming tasks

  • Master file handling techniques in both Python and R, including reading and writing files, accepting user input, and handling command-line arguments to enhance program flexibility and interactivity

Module 2: Python & R programming languages

  • Understand different types of datasets and data generation methods used in bioinformatics, as well as common public databases in the field

  • Develop proficiency in using industry-standard tools and libraries for processing and analysing biological data

  • Omics Data Analysis - Tools, Outcomes, Use Cases and Applications

Module 3: Data analysis & visualization

  • Demonstrate proficiency in managing and analysing data by utilising different types of biological databases, applying appropriate database management systems, and implementing data security and privacy measures

  • SQL (structured query language) for relational databases. Master the fundamental concepts and principles of SQL, including syntax, data types, data manipulation, and database management.

  • Apply advanced SQL concepts such as joins, subqueries, views, stored procedures, and functions to query and aggregate data from multiple tables, optimise query performance, and solve real-world data-related problems.

Module 4: Data architecture & database management

  • Build a strong foundation in biostatistics by applying key concepts, such as variability, population, sample, central tendency, and variability, in order to analyse and interpret biological data using descriptive statistics techniques.

  • Apply inferential statistics techniques, such as hypothesis testing and confidence interval construction, to make statistical inferences and draw conclusions about populations based on sample data.

  • Design and implement biotechnology experiments using appropriate experimental design principles, including randomization, replication, and blocking, to ensure reliable and valid results.

Module 5: Introduction to Statistics in Biotechnology

  • Explain the fundamental concepts of Artificial Intelligence (AI) and Machine Learning (ML), including their different types and applications.

  • Implement common Machine Learning algorithms (e.g. Linear Regression, Decision Trees) using popular libraries like scikit-learn to analyse biological data and interpret the results.

  • Critically evaluate the strengths and limitations of Deep Learning architectures (e.g., CNNs, RNNs) for specific bioinformatics tasks, considering tools like TensorFlow and PyTorch for implementation.

Module 6: AI & ML in Biotechnology

Download detailed syllabus

Concepts covered

Tools you will use to learn

Brush up your basics & get started

What can you expect ?

720 hours of technical learning

48 hours of soft-skill building

1 capstone industry project

2 weeks of hackathons, workshops & bootcamps with the industry

100% Placement Assistance

Dedicated career support and guidance to help

students land at Top Tech Companies

40+ Career Specialists

To ensure a portfolio and industry CV is built for a biotechnologist

80 Career Partners

Giving students the choice of a stellar lineup to start their biotech career!

Placements at Bversity School of Biotechnology

AWArD WINNING EDTECH STARTUP OF THE YEAR 2023

Bversity School of Biotechnology

At Bversity, we are proud to be a pioneer in Biotech education space, dedicated to

delivering a world-class educational experience that blends quality, innovation, skills and flexibility. All our learning

programs are fully accredited, adhering to the rigorous standards of Atria University, Bangalore.

Bversity + Atria University

Bversity School of Biotechnology has partnered with the Atria University, Bangalore in running the PG programs successfully & accredits the courses.

Frequently asked questions

1. What is the duration of the Industry PGP Bioinformatics course?

The course duration is 12 months.

2. What is the course structure like?

3. How is the Industry PGP Bioinformatics course better than a regular 2-year masters program?

4. Are there any prerequisites for this course?

5. What are the key highlights of this course?

6. Who is this course suitable for?

7. How can I apply for admission?

8. How can I get more information about the course?

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