Masters in Data Science

A Masters in Data Science course helps you advance your career while balancing work or other commitments. It offers flexible formats, including fully online and hybrid learning.

The course provides a globally recognized degree, an industry-relevant curriculum, and career support to prepare you for success in the data science field.

These are some of your top choices:

1. Masters Degree in Artificial Intelligence and Data Science

Provided By: O.P Jindal University

Mode: Online

Duration: 12 months

Fees: INR 2.75L

Overview

A one-year online Master’s in AI and Data Science that provides deep expertise in machine learning, Python, business analytics, and generative AI. The program offers foundational prep for non-coders, dual specializations in Business Analytics or Machine Learning & AI, and 30+ real-world projects to develop practical, industry-ready skills.

Highlights

• 30+ case studies, industry-aligned capstone projects, and 15+ tools covered

• Dual specialization: Business Analytics or Machine Learning & AI

• Complementary Microsoft Certification included

• Expert mentorship and comprehensive career support

2. Masters in Data Science

Provided By: Liverpool John Moores University

Mode: Online

Duration: 18 months

Fees: INR 5.20L

Overview
A globally accredited Master’s in Data Science that builds expertise in Python, R, SQL, AI, machine learning, big data, and data visualization. The course combines theory with hands-on projects and real-world case studies to prepare learners for high-impact data roles.

Highlights

• Dual certification with MSc from LJMU and Executive Diploma

• 60+ real-world case studies and 14+ hands-on projects

• Mentorship from industry experts and personalized coaching

• Microsoft certification included

A Masters in Data Science helps you build strong technical and analytical skills that are in high demand across industries. With India becoming one of the world’s fastest-growing digital economies, data science has become a key skill for professionals who want to build a future-proof career in analytics, AI, and machine learning.

Top Reasons to Pursue a Masters in Data Science in India

1. India’s Data-Driven Economy Is Growing Fast:

• India’s digital transformation is driving massive demand for skilled data professionals. Every sector from banking and healthcare to retail and logistics is using data to make smarter business decisions.

• According to NASSCOM, India’s data and AI market is expected to add over 1 million new jobs by 2026.

2. High Demand Across Multiple Industries:

• Organizations in finance, e-commerce, telecom, and manufacturing are investing heavily in analytics and AI. This has created a strong job market for data scientists, analysts, and machine learning engineers across the country.

3. Strong Salary Growth Potential:

• Data science roles offer excellent salary packages. According to AmbitionBox, the average salary for a Data Scientist in India is approximately INR 15.1 LPA, depending on experience and company.

• Professionals with a master’s degree often earn 20–30% more than those without one.

4. Expanding Career Opportunities:

• According to The Economic Times, 11.5 million data science jobs will be created globally by 2026. This shows the massive global demand for data professionals, with India being one of the leading markets in this growth.

• Graduates can work as Data Scientists, Machine Learning Engineers, BI Analysts, or Data Engineers.

5. Global Recognition and Flexibility:

• Many universities in India now offer globally recognized online and hybrid master’s programs in data science.

• This gives learners the flexibility to study while working and earn a valuable credential from reputed institutions.

Eligibility and admission requirements for a Masters in Data Science may vary across different universities and programs. Here, we provide the general criteria and process that most institutes follow to help you understand if you qualify and what to expect during admission.

Eligibility

To apply for a Masters in Data Science, candidates generally need:

• A Bachelor’s degree in Engineering, Science, Mathematics, or a related field.

• Basic knowledge of programming (Python, R, or SQL) and statistics is preferred.

• Some programs may consider candidates with work experience in analytics or data-driven roles.

Meeting these general requirements ensures you can comfortably follow the course and handle advanced data science topics.

Admission Process

Most universities follow a structured admission process for the Masters in Data Science:

1. Fill Application Form: Submit your academic details and personal information online.

2. Screening / Aptitude Test: Some programs may require a short test to evaluate your analytical and technical skills.

3. Interview & Offer Letter: Selected candidates may be interviewed by faculty or program coordinators before receiving the admission offer.

4. Enrollment Confirmation: Once accepted, complete the enrollment process and payment to secure your seat.

Following this process ensures a smooth start to your Masters in Data Science journey, preparing you for a rewarding career in analytics, AI, and machine learning.

The Masters in Data Science curriculum is designed to give you a strong foundation in both theory and practical skills. It covers all essential areas of data science, ensuring you are ready to handle real-world data challenges and advance your career in analytics, AI, and machine learning.

Course Curriculum:

The program typically includes the following modules:

• Foundations of Data Science: Basics of data, statistics, probability, and analytics concepts.

• Python and R Programming: Learn programming languages widely used in data science for analysis, modeling, and automation.

• Machine Learning: Study algorithms and techniques for predictive modeling and data-driven decision making.

• Deep Learning & AI: Explore neural networks, computer vision, NLP, and AI applications.

• Big Data Analytics: Work with large datasets using Hadoop, Spark, and cloud-based tools.

• Data Visualization (Power BI, Tableau): Learn to create dashboards and visualizations to communicate insights effectively.

• Business Analytics & Decision Science: Understand how to use data to make strategic business decisions.

• Capstone Project / Thesis: Apply your learning to a real-world problem, creating a project that showcases your skills.

Skills You Will Learn:

• Data analysis and statistical modeling

• Machine learning and AI implementation

• Big data handling and cloud computing

• Business analytics and strategic decision-making

• Data visualization and storytelling

Tools You Will Learn:

• Programming & Analytics: Python, R, SQL

• Machine Learning & AI: TensorFlow, PyTorch, Scikit-learn

• Big Data: Hadoop, Spark

• Visualization & BI: Power BI, Tableau

When choosing a Masters in Data Science, understanding the program duration and learning format is important. Different universities offer flexible options to suit your schedule, whether you prefer full-time, online, or hybrid learning.

Knowing this helps you plan your time and balance studies with work or other commitments.

Program Duration and Learning Modes:

A Masters in Data Science opens doors to some of the most in-demand and high-paying roles in the tech and analytics industry. Graduates gain skills in AI, machine learning, data engineering, and business analytics, making them valuable assets for top companies across multiple sectors.

Top Job Roles and Average Salaries:

Source: Ambition Box

Top Recruiters

Graduates can be recruited by leading companies in tech, finance, consulting, and analytics sectors, including:

• Amazon

• Deloitte

• Accenture

• TCS

• Microsoft

• KPMG

Choosing the right platform for your Masters in Data Science is crucial for gaining practical skills, industry exposure, and career opportunities. upGrad offers a comprehensive program designed to help learners become industry-ready while providing support and guidance throughout the learning journey.

Advantages of upGrad’s Masters in Data Science Program

1. Personalized Mentorship: Get guidance from experienced faculty and industry experts who help you navigate complex concepts and career decisions.

2. Industry-Aligned Projects: Work on real-world projects that are designed by top companies, giving you hands-on experience with tools and technologies used in the field.

3. Job Placement Support: upGrad provides dedicated career services, including interview preparation, resume building, and placement assistance, to help you land top data science roles.

4. Flexible Learning Modes: Choose from online, hybrid, or live classes to balance your studies with work or other commitments, making it easier to pursue a this degree without disrupting your schedule.

5. Alumni Network & Success Stories: Become part of a strong community of alumni who have successfully advanced their careers, providing networking opportunities and inspiration for your own journey.