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Masters of Science in Data Science and Analytics


OPEN


2 years


Full-time

Entry Requirements
ANY Bachelor’s Degree (except BA) with minimum aggregate of 50%

Programme Highlights

A comprehensive educational pathway featuring triple majors in Biotechnology, Biochemistry, and Genetics.

  • Acquire sought-after skills in data analytics, meeting industry demands.
  • Blend of mathematics, statistics, computing, and domain expertise.
  • Covering core areas like AI, machine learning, big data, and more.
  • Gain hands-on experience through real-life problem-solving projects.
  • Emphasize professional ethics, societal concerns, and environmental responsibilities.
Read more
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Course Structure

Semester 1

Course Title

  • Core Java
  • Advanced Database Management System
  • Artificial Intelligence
  • Statistical Analysis
  • Research Methodology

Semester 2

Course Title

  • Python Programming
  • Software Testing and Quality Assurance
  • Cloud Computing
  • Data Mining and Analytics
  • Mathematical Foundation for Data Science

Semester 3

Course Title

  • Robotic Process Automation
  • Big Data Analytics
  • Design Thinking
  • Neural Networks and Deep learning
  • Programming in R for Data Analytics

Semester 4

Course Title

  • Internship
  • Dissertation

Semester 5

Course Title

  • Internship

Elective-I

  • Introduction to Data Science
  • Social Network Analysis
  • Deep learning & Natural Language Processing
  • Data Privacy and Data Security (CS)

Elective-II

  • Cryptography and Network Security(CS)
  • Micro-Controllers
  • Devops
  • Introduction to Robotics

Semester 6

Course Title

  • Plant Biotechnology
  • Plant Biotechnology (P)
  • Bioprocess Technology
  • Bioprocess Technology (P)
  • Enzymology
  • Enzymology (P)
  • Nutrition & Dietetics
  • Nutrition & Dietetics (P)
  • Behavioral Neurogenetics
  • Behavioral Neurogenetics (P)
  • Population Genetics & Biometry
  • Population Genetics & Biometry (P)
  • Research Methodology

Elective-III

  • Prompt Engineering & Generative AI
  • Vulnerability Assessment and Penetration Testing
  • Gaming Design (AI)
  • Embedded System Design

Elective – IV

  • Blockchain Technologies
  • Neural Networks and Fuzzy Systems
  • Security information and event management
  • Sensors and Actuators

Semester 7

Course Title

  • Mobile Application Development
  • Innovation & Entrepreneurship Management
  • Elective – V
  • Skill Enhancement Course
  • Project Management with Git
  • Open Elective-I
  • Project Phase – I

Semester 8

Course Title

  • Seminar
  • Internship
  • Capstone Project

In addition to the above courses, our curriculum includes the following courses powered by Coursera and industry partners.

Semester 1

Certificate courses by University /Industry Partner

Single Page Web Applications with AngularJS

Database Management Essentials

Introduction to Genetics and Evolution

C for Everyone: Programming Fundamentals

Operating Systems Fundamentals

Introduction to Electronics

Economics of Money and Banking

English for Science, Technology, Engineering, and Mathematics

Successful Presentation

Semester 2

Certificate courses by University /Industry Partnerx

Cloud Computing Applications, Part 1: Cloud Systems and Infrastructure

Cloud Computing Concepts, Part 1

The Bits and Bytes of Computer Networking

C++ For C Programmers, Part A,Part B

Introduction to Back-End Development

Computer Architecture

Modern Art & Ideas

Write Professional Emails in English

Semester 3

Certificate courses by University /Industry Partner

The Science of Stem Cells

Fundamentals of Immunology: Innate Immunity and B-Cell Function

Databases and SQL for Data Science with Python

Using Databases with Python
Cloud Computing Concepts: Part 2

Career Decisions: From Insight to Impact

Semester 4

Certificate courses by University /Industry Partner

Drug Discovery

DNA DECODED      

Bioinformatics I- Finding Hidden Messages in DNA

Genome Sequencing (Bioinformatics II)

Visual Analytics with Tableau
Applications of Everyday Leadership

Learn to Speak Korean 1

Semester 5

Certificate courses by University /Industry Partner

Semester 6

Certificate courses by University /Industry Partner

Introduction to Industrial Bioprocess Development

Healthy Practices: Nutrition, Physical Activity, and Community and Family Participation

Sleep: Neurobiology, Medicine, and Society

Disease Screening in Public Health

Fee Structure for the Academic Year 2025-26

Domestic / NRI Fee Structure

Programmes

MSDA

Course Duration

2 years

1st Installment

INR 65,000

3 Subsequent Installments

INR 89,000

 

International Fee Structure

Programmes

MSDA

Course Duration

2 years

1st Installment

$ 1500

5 Subsequent Installments

$ 1000

OTHER FEES

CAUTION DEPOSIT : Rs. 5000/- to be paid by all the  students.

(Rs 3000/- will be refunded deducting incidental expenses and alumni membership.)

EXAMINATION FEES PER SEMESTER

PG Programs: Rs.3500/-

Job Opportunities

  • Process Associate
  • MIS Executive
  • Finance Executive
  • Back Office Executive
  • Accountant
  • HR assistant
  • Financial Analyst
  • Account Assistant
  • Accounts Executive
  • Banker
  • Stock Broker
  • Export-import Manager
  • Tax consultant
  • Finance Consultant
  • Insurance Consultant
  • Entrepreneur

Career Path

After completing a M.Sc. Data Science and Analytics at Garden City University (GCU), these are some of the most trending career opportunities:

Data Scientist: Analyzing and interpreting complex datasets to inform business decision-making. Data scientists use statistical techniques, machine learning, and programming skills to extract insights and build predictive models.

Data Analyst: Focusing on interpreting and analyzing data to help organizations make informed decisions. Data analysts work with databases, statistical tools, and visualization techniques to present findings.

Business Intelligence (BI) Analyst: Using data analysis tools to provide insights into business performance. BI analysts create reports and dashboards to assist organizations in strategic planning.

Read more

List of companies where UG & PG Commerce and Management students of GCU got placement opportunities:

Biocon, Syngene, LifeCell, Cryoviva, HCG, Indigene, Anand Diagnostics, Indo-American Hybrid Seeds, Molecular Connections, Dr. Reddy’s Laboratories.

Programme Highlights
  • Acquire sought-after skills in data analytics, meeting industry demands.
  • Blend of mathematics, statistics, computing, and domain expertise.
  • Covering core areas like AI, machine learning, big data, and more.
  • Gain hands-on experience through real-life problem-solving projects.
  • Emphasize professional ethics, societal concerns, and environmental responsibilities.
  • Master data analytics principles, statistical methods, and Python programming for comprehensive problem-solving.
  • Develop expertise in mathematical foundations, database technologies, and data mining for robust analytics.
  • Acquire in-depth knowledge of AI, regression modelling, and big data analytics for advanced problem analysis and solution design.
  • Explore machine learning, natural language processing, and data visualization, enhancing skills crucial for modern analytics applications.
  • Apply research-based knowledge in project management, emphasizing professional ethics, cyber regulations, and responsible computing practices.
  • Choose from a range of elective courses, including business intelligence, IoT, web analytics, and cloud analytics.
Programme Highlights
  • M.Sc. in Data Science and Analytics

    After completing a M.Sc. Data Science and Analytics at Garden City University (GCU), these are some of the most trending career opportunities:

    Data Scientist: Analyzing and interpreting complex datasets to inform business decision-making. Data scientists use statistical techniques, machine learning, and programming skills to extract insights and build predictive models.

    Data Analyst: Focusing on interpreting and analyzing data to help organizations make informed decisions. Data analysts work with databases, statistical tools, and visualization techniques to present findings.

    Business Intelligence (BI) Analyst: Using data analysis tools to provide insights into business performance. BI analysts create reports and dashboards to assist organizations in strategic planning.

    Machine Learning Engineer: Building and implementing machine learning algorithms and models. Machine learning engineers work on developing systems that can learn and adapt without explicit programming.

    Big Data Engineer: Designing, developing, and maintaining large-scale processing systems for big data. Big data engineers work with tools like Hadoop and Spark to handle and process massive datasets.

    Data Engineer: Building, testing, and maintaining data architecture (databases, large-scale processing systems) for efficient data retrieval and storage.

    Quantitative Analyst: Applying statistical and mathematical models to analyze financial data, often in the context of risk management and investment strategies.

    Predictive Modeler: Developing models to predict future trends or outcomes based on historical data. This role is prevalent in marketing, finance, and healthcare.

    Data Architect: Designing and creating data systems and structures for organizations. Data architects ensure that databases and systems are optimized for data storage and retrieval.

    Business Analytics Manager: Overseeing analytics initiatives within an organization, ensuring that data-driven insights contribute to strategic decision-making.

    Research Scientist: Conducting research and experiments to develop new algorithms and methodologies in the field of data science and analytics.

    Data Consultant: Providing expert advice on data-related matters to businesses, helping them optimize their data strategies and implementations.

    Healthcare Data Analyst: Applying data analytics in the healthcare sector to improve patient outcomes, optimize operations, and support medical research.

    Fraud Analyst: Using data analytics to detect and prevent fraudulent activities in various industries, such as finance and e-commerce.

    Cybersecurity Analyst (with a focus on Data): Analyzing data to identify and prevent security threats and breaches.