Overview

Over the past few decades, environmental and life-style associated diseases have been on the rise deeply impacting human health. The genetic impacts of many diseases remain largely unexplored. Due to expensive clinical trials and challenges that we face due to the rapid growth of antimicrobial resistance, alternative therapies and strategies to combat antimicrobial resistance are the need of the hour. DNA sequencing has emerged as an indispensable tool to enhance our understanding of the genetic basis of human disease and effective use of that knowledge to improve human health. Furthermore, Genome-wide association studies have provided substantial knowledge in understanding common variants associated with diseases. However, there is more to learn about the disease heritability and mechanisms for many of such findings.

Given the large amount of data generated from these experiments, substantial expertise is required to handle and analyze them in order to establish and elucidate the genetic basis of diseases through Bioinformatics. This can be made possible by integrating good knowledge of Big Data processing platforms along with programming skills, bringing in huge demand for trained personnel as Data Scientists. The mLAC in collaboration with Molsys Scientific seeks to provide a platform to Life Science graduates to transform/initiate their careers as potential Genome data Scientists, through this unique Post Graduate Diploma program in Genomics and Cloud Computing.

Nomenclature of the course

Advanced PG Diploma Program Genomics and Cloud Computing

Objectives

1. To enhance the employability of the candidate by equipping the candidate with the essential skills in both Genome Informatics and Data sciences, particularly data generated from sequencing platforms

2. Enhance understanding of the basics of molecular biology, genome organization and their functional elements. Enhance knowledge of the differences in the genes/genomes of different species

3. To explore the principles and practical applications of the major analytical techniques used in molecular biology

4. Evaluate current experimental approaches

5. Enhance understanding and latest advances in sequencing technologies

6. Enhance skills with reading primary literature

7. Develop a strong foundation working on Linux platforms

8. Enhance programming skills using Scala, Biopython, Tableau, R, MS Excel (Intermediate level)

9. Develop a thorough foundation in Statistics and data visualization using R and MS Excel

10. Develop key skills in Data Analytics and Machine learning

11. Enhance Data Mining skills using latest tools

12. Understanding handling Big Data and developing skills in Big Data processing tools and file systems based on knowledge in Hadoop and Spark

13. Understanding of Cloud computing, learning to develop, deploy and scale-up applications on the Cloud. Data security and data management in virtual platforms.

Eligibility

Candidate must have secured 40% in aggregate and completed a four-year bachelor degree in any of the science stream or post-graduation in any of the science stream. B.Tech/M.Tech (Biotechnology/Bioinformatics/CS/IT), MBBS, MCA, BSc/MSc. ( Any Life Sciences discipline or Computer Science ), PhD (Life Sciences/ Machine Learning/Statistics/Computer Science).

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Cognate Subjects

Affiliations

Bengaluru City University

Career Prospects

NGS data career paths encompass both data management and data analysis roles.

Database developers and administrators develop and maintain the IT infrastructure that supports big data. Other roles focus on using big data to generate actionable insights organizations can use in decision making, strategic planning and business development.

1. Database Administrator

Average Salary Range: $98,000 – $140,000

Database administrators are responsible for the integrity, performance and security of a database. Their duties include everything from planning databases to troubleshooting and monitoring them to ensure data security.

2. Database Developer

Average Salary Range: $70,000 – $100,000

Database developers modernize, upgrade and design databases. They may eliminate inefficient coding to improve database performance and monitor, troubleshoot and debug database issues.

3. Data Analyst

Average Salary Range: $77,000 – $118,000

After the database is housed, grouped and managed, it’s time to analyze it. That’s where big data analysts come in.

Data analysis is one of the more common big data occupations. Data analysts collect, analyze and perform statistical data analysis, working with large volumes of data to turn it into business insights their team members can use.

4. Data Scientist

Average Salary Range: $90,000 – $110,000

Data scientists understand data from a business point of view.

They go a step beyond standard statistical analysis to create new algorithms to analyze and utilize data. They build statistical models and utilize advanced programming skills to identify high-level business trends and insights.

5. Big Data Engineer

Average Salary Range: $95,000 – $150,000

There is significant overlap between data engineer and data scientist roles.

Data scientists are heavily involved in using the data infrastructure, but they aren’t responsible for maintaining it.

Data engineers are focused on the products that support data scientists’ work. They design and manage how data is housed and build scalable, high-performance infrastructure that delivers cohesive information from raw data sources.

6. Data Modeler

Average Salary Range: $111,000 – $160,000

A data model is a representation of the business and information needs in an enterprise.

Data modellers turn business requirements into conceptual and physical data models. They could reduce redundancy of data within a computer system or improve how it’s transferred between users an organization.

Employability

The course is designed to equip B.Sc./M.Sc. students with knowledge on certain key aspects of Biotechnology: Genomics and high-throughput platforms such as Next Generation Sequencing (NGS), Microarray and their applications, bioinformatics, programming, statistics and data analytics.

Program Outcome

This course imparts a combination of basic and advanced knowledge on genomics, genome organization across life, next-generation methods to study genome, transcriptome and epigenome of eukaryotic or prokaryotic organisms and in different applications of genomics science. It also focuses on the interdependence and multidisciplinary aspects of all these technologies. Towards the completion of this course, the candidate would have a strong understanding of sequencing data from high-throughput platforms and strong programming knowledge with an emphasis on the researchers’ ability to handle, analyse and store data efficiently. This course would focus on the practical applications of such techniques and thus facilitate better interpretation of genome sequencing results. Candidates gain work experience simultaneously engaging with Industrial projects alongside their training which enhances their placement opportunities with attractive salary packages. The course would aim at enabling a student with essential skills in data analytics and thereby transforming the candidate into a potential Genomics Data Scientist.

Syllabus

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Post Graduate Diploma in Genomics and Cloud Computing