Program Review
The M.Sc. in Data Science at Atharva University, Mumbai is a rigorous postgraduate program designed to develop advanced expertise in Data Analytics, Artificial Intelligence, and Large-Scale Data Systems. The program emphasizes Research-Driven Learning, Analytical Depth, and Real-world problem solving, preparing graduates to excel in high-impact roles across industry and academia.
Students acquire strong foundations in Machine Learning, Deep Learning, Natural Language Processing, Big Data Engineering, and Cloud-Based Analytics, complemented by hands-on experience with modern AI ecosystems. Through Practical Laboratories, Industry-Oriented Projects, Internships, and a Mandatory Dissertation, learners gain exposure to scalable data architectures and intelligent system design.
The curriculum is structured to nurture Critical Thinking, Innovation, and Leadership capabilities, enabling graduates to address complex data challenges and contribute meaningfully to data-driven decision-making in global organizations or pursue advanced research and doctoral studies.
Duration & Eligibility
Requirements and selection process for the M.Sc. Data Science Program
Duration
2 Years
Eligibility
Passed any graduation degree (e.g.: B.E. / B.Tech./ B.Sc / B.Com. / B.A./ B. Voc./ BCA etc.,) preferably with Mathematics at 10+2 level or at Graduation level. Obtained at least 50% marks (45% marks in case of candidates belonging to reserved category) in the qualifying examination. For students having no Mathematics background, a compulsory bridge course related to computer subjects will be provided as per the norms.
Selection Process
Valid Score of MH CET 2026 / PERA CET 2026 / CUET 2026 / Atharva University All India Entrance Test and Personal Interview.
Programme Highlights
Advanced Curriculum
- Artificial Intelligence, Machine Learning & Deep Learning
- Big Data Analytics & Distributed Computing
- Cloud Analytics & Predictive Modelling
Hands-on Technical Training
- Apache Spark & Hadoop ecosystems
- AWS, Azure Machine Learning & Cloud Platforms
- Advanced Python libraries, Tableau & Data Visualization Tools
Industry & Research Exposure
- Industry-led workshops and expert guest lectures
- Case-study-based learning and real-world datasets
- Project Day – Every Friday (Hands-on Learning & Portfolio Building)
- Research projects and dissertation work
State-of-the-Art Infrastructure
- Real-time analytics laboratories
- Big data processing and Cloud-enabled environments
- Apple Vision Pro for AR/VR Research, Simulation and Immersive Learning
- India’s First Research-Gate Robotic Lab
Career & Professional Development
- Internship (Mandatory or Credit Based)
- Placement support
- Guidance for research publications and Ph.D. preparation
Career Support & Opportunities
Graduates of the M.Sc. Data Science program are well-equipped to pursue dynamic and high-growth career roles across multiple sectors, including IT and software services, consulting firms, banking and financial institutions, e-commerce and retail organizations, healthcare and life sciences, marketing and digital media agencies, manufacturing industries, and government analytics departments. Graduates may also opt for postgraduate studies and research in Data Science, Artificial Intelligence, Analytics, Computer Science, or Management.
Data Analyst
Business Analyst
Associate / Junior Data Scientist
Machine Learning Engineer
Big Data Engineer
Research Analyst
AI & Analytics Associate
Programme Outcomes
On successful completion of the program, graduates will be able to:
Apply advanced AI, machine learning, and deep learning techniques to solve complex real-world data problems.
Demonstrate strong research aptitude, innovation skills, and analytical reasoning.
Design and manage scalable big data architectures and cloud-based analytics solutions.
Develop intelligent, secure, and high-performance data-driven systems.
Exhibit leadership readiness for strategic and decision-making roles in data-centric environments.
Curriculum Highlights
Explore the key subject areas, emerging technologies, and hands-on learning opportunities covered in the M.Sc. Data Science programme.
Programming & Data Management
Programming Languages
- Advanced Python Programming
- R Programming
- Data Structures & Algorithms using Python
- Object-Oriented Programming Concepts
Database Management
- Advanced Database Management Systems (DBMS)
- SQL for Data Science
- Data Engineering Fundamentals
Core Data Science & Analytics
Data Analytics
- Data Analytics using Excel
- Exploratory Data Analysis (EDA)
- Predictive Analytics
- Business Analytics & Decision Intelligence
Visualization & Statistics Tools
- Data Visualization (Tableau & Power BI)
- Statistical Analysis using SPSS & SAS
Mathematics & Statistics
Mathematical Foundations
- Descriptive Statistics
- Probability & Statistical Distributions
- Linear Algebra
Statistical Methods
- Statistical Methods for Data Science
- Hypothesis Testing
- Time Series Analysis
Artificial Intelligence & Machine Learning
AI & Machine Learning
- Artificial Intelligence
- Machine Learning Algorithms
- Deep Learning
- Generative AI
AI Development
- TensorFlow for AI Development
- AI Model Development & Deployment
Emerging Technologies
Big Data & Cloud Computing
- Big Data Analytics
- PySpark for Large-Scale Data Processing
- Cloud Computing (AWS, Azure & Databricks)
Intelligent Technologies
- Natural Language Processing (NLP)
- Computer Vision
- Robotic Process Automation (RPA)
Next-Generation Technologies
- Blockchain Technology
- Internet of Things (IoT)
- Augmented Reality (AR) & Virtual Reality (VR)
Hands-on Learning & Industry Exposure
Industry Experience
- Industry-Oriented Projects & Internships
- Real-World Business Case Studies
- Exposure to Real Business Datasets & Challenges
- Industry Expert Sessions & Workshops
Research & Projects
- Research-Oriented Learning
- AI & Data Science Capstone Projects
- Hackathons & Coding Competitions
- GitHub Portfolio Development
State-of-the-Art Infrastructure
The programme highlights specialised facilities and technology-enabled environments supporting research, simulation, analytics, and practical learning.
Real-Time Analytics Laboratories
Big Data Processing Environments
Cloud-Enabled Environments
Apple Vision Pro for AR/VR Research, Simulation and Immersive Learning
India’s First Research-Gate Robotic Lab
Questions?
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01 What is the duration of the M.Sc. Data Science programme?
The M.Sc. Data Science programme at Atharva University, Mumbai, has a duration of 2 years.
02 What are the eligibility criteria for M.Sc. Data Science?
Candidates must have passed a graduation degree such as B.E., B.Tech., B.Sc., B.Com., B.A., B.Voc. or BCA, preferably with Mathematics at the 10+2 or graduation level. A minimum of 50% marks is required, with 45% for candidates belonging to reserved categories. Students without a Mathematics background must complete a compulsory bridge course related to computer subjects as per the norms.
03 What is the selection process for admission?
The selection process includes a valid score in MH CET 2026, PERA CET 2026, CUET 2026, or the Atharva University All India Entrance Test, followed by a Personal Interview.
04 What subjects are covered in the curriculum?
The curriculum covers a wide range of areas, including:
- Advanced Python Programming and R Programming
- Data Analytics, Statistics and Data Visualization
- Artificial Intelligence and Machine Learning
- Deep Learning and Generative AI
- Big Data Analytics and Cloud Computing
- Natural Language Processing and Computer Vision
- Blockchain, IoT, AR/VR and Robotic Process Automation
05 Does the programme include practical learning?
Yes. The programme includes practical laboratories, industry-oriented projects, real-world datasets, case studies, hands-on technical training, and research-oriented learning.
06 Are internships part of the M.Sc. Data Science programme?
The programme highlights industry-oriented projects and internships. Internships are described as mandatory or credit-based.
07 Does the programme include research and dissertation work?
Yes. The programme includes research projects and a mandatory dissertation, with an emphasis on research-driven learning, analytical depth, and intelligent system design.
08 What career opportunities are available after graduation?
Graduates may pursue roles such as:
- Data Analyst
- Business Analyst
- Associate / Junior Data Scientist
- Machine Learning Engineer
- Big Data Engineer
- Research Analyst
- AI & Analytics Associate
09 Which industries can M.Sc. Data Science graduates work in?
Career opportunities exist in IT and software services, consulting, banking and finance, e-commerce and retail, healthcare and life sciences, marketing and digital media, manufacturing, and government analytics departments.
10 Which tools and technologies are covered?
The programme highlights Apache Spark, Hadoop, AWS, Azure Machine Learning, Python libraries, Tableau, Power BI, SPSS, SAS, TensorFlow, PySpark, Databricks, and other emerging technologies.
11 Does the programme provide placement support?
Placement support is included among the programme's career and professional development highlights.
12 Can graduates pursue doctoral studies?
Yes. The programme is designed to prepare graduates for advanced research and doctoral studies, with guidance for research publications and Ph.D. preparation.
13 What makes the M.Sc. Data Science programme distinctive?
The programme combines advanced data science subjects, AI and cloud technologies, practical laboratories, industry-oriented projects, research exposure, a mandatory dissertation, and professional development opportunities.