Master of Science in Computer Science
Specialization in Data Analytics & Machine Learning
Accredited Institution
Quality assured education
Data Science Labs
GPU-powered computing
Placement Record
Top tech companies recruit
Live Projects
Real-world data experience
Programme Overview
The Master of Science in Computer Science with specialization in Data Analytics is a comprehensive two-year postgraduate programme designed to transform Learners into skilled data professionals. This UGC-recognized programme offers an intensive blend of advanced computer science concepts, statistical analysis, machine learning algorithms, and cutting-edge big data technologies, preparing graduates for leadership roles in the rapidly evolving field of data science.
Our progressive education philosophy emphasizes experiential learning through industry projects, research dissertations, and hands-on work with real-world datasets. The curriculum integrates theoretical foundations with practical applications using Python, R, SQL, TensorFlow, and cloud platforms like AWS and Azure, equipping graduates with the analytical skills demanded by leading technology companies, consulting firms, and research organizations worldwide.
Eligibility & Admission Criteria
Requirements for joining the M.Sc Computer Science (Data Analytics) programme
Academic Qualification
- •Bachelor's degree from recognized university
- •B.Sc Computer Science / IT / BCA
- •Minimum 55% aggregate marks
- •50% for reserved categories
Accepted Disciplines
- •B.Sc Computer Science / IT
- •BCA / B.Sc Mathematics
- •B.Sc Statistics / Physics
- •B.E/B.Tech (Any branch with Mathematics)
Documents Required
- •UG Degree Certificate & Mark Sheets
- •Transfer Certificate
- •Migration Certificate
- •Community Certificate
- •Passport Size Photographs
- •Aadhaar Card Copy
Programme Curriculum
Comprehensive syllabus designed to build expertise in data analytics and machine learning
Semester I
- •25PDAC01 – Descriptive Statistics
- •25PDAC02 – Foundations of Data Science
- •25PDAC03 – Linear Algebra
- •25PDACP01 – Oracle and SQL Lab
- •25PDACP02 – Data Analytics Lab I (R, SPSS, SciLab)
- •25PDAE01 / 25PDAE02 – Data Structures / Information Retrieval
- •25PDAE03 / 25PDAE04 – RDBMS and SQL / Information Security
Semester II
- •25PDAC04 – Machine Learning
- •25PDAC05 – Big Data Framework
- •25PDACP03 – Data Analytics Lab II (Hadoop, Map Reduce & R, SPSS)
- •25PDACP04 – Machine Learning and Python Lab
- •25PDAE05 / 25PDAE06 – Data Science with Python / Web Data Analytics
- •25PDAE07 / 25PDAE08 – Social Media Analytics / Customer Analytics
- •Extra Disciplinary Course [EDC] – I
- •25PHR001 – Fundamental Study of Human Rights
Programme Learning Outcomes
Skills and competencies you will develop through this programme
Data Engineering Expertise
Design and implement robust data pipelines, ETL processes, and data warehousing solutions using modern big data technologies like Hadoop, Spark, and cloud platforms.
Machine Learning Proficiency
Build, train, and deploy machine learning models for classification, regression, clustering, and predictive analytics using scikit-learn, TensorFlow, and PyTorch frameworks.
Statistical Analysis Skills
Apply advanced statistical methods, hypothesis testing, regression analysis, and probability theory to derive actionable insights from complex datasets.
Data Visualization Mastery
Create compelling visualizations and interactive dashboards using Tableau, Power BI, Matplotlib, and D3.js to communicate insights effectively to stakeholders.
Deep Learning Capabilities
Implement deep neural networks, CNNs for computer vision, RNNs for sequence modeling, and transformers for NLP applications using cutting-edge frameworks.
Professional Communication
Effectively communicate analytical findings through technical reports, executive presentations, and data storytelling while collaborating in cross-functional teams.
Career Opportunities
Diverse career pathways await M.Sc Data Analytics graduates
Data Scientist
Build predictive models and derive insights at tech giants and startups
ML Engineer
Design and deploy machine learning systems at scale
Business Intelligence Analyst
Transform data into strategic business decisions
Data Engineer
Build robust data pipelines and infrastructure
Research Scientist
Advance AI research at labs and universities
Analytics Consultant
Strategic consulting at Big 4 and tech consultancies
Product Analyst
Drive product decisions with data at tech companies
AI Specialist
Develop cutting-edge AI solutions for enterprises
Key Employment Sectors
Department Facilities
State-of-the-art infrastructure supporting world-class data science education
High-Performance Computing Lab
GPU-powered workstations with NVIDIA Tesla cards, 128GB RAM systems, and high-speed SSD storage for deep learning and big data processing.
Cloud Computing Infrastructure
Access to AWS, Azure, and Google Cloud Platform with dedicated educational credits for Learners to deploy and scale analytics solutions.
Big Data Analytics Cluster
Dedicated Hadoop and Spark cluster for processing terabytes of data, enabling hands-on experience with distributed computing frameworks.
Enterprise Software Suite
Licensed access to Tableau, Power BI, SAS, SPSS, MATLAB, and industry-standard analytics tools for comprehensive learning experience.
Research & Innovation Center
Dedicated space for dissertation work, industry collaborations, and research projects with mentorship from industry experts and Learning Facilitators.
Digital Library & Resources
Access to IEEE, ACM, Springer, and other academic databases with thousands of research papers, journals, and e-books on data science topics.
Why Choose Our M.Sc Data Analytics Programme?
Our progressive education approach ensures holistic development, preparing you for success in the data science industry.
UGC Recognized & NAAC Accredited
Quality-assured education meeting national standards with excellent academic reputation.
Industry-Ready Curriculum
Aligned with industry trends covering Python, R, machine learning, big data, and cloud computing.
Advanced Lab Infrastructure
GPU-powered computing labs with access to AWS, Azure, and Google Cloud Platform.
Expert Learning Facilitators
Highly qualified faculty with doctoral degrees and industry experience in data science.
Strong Industry Connections
Partnerships with leading tech companies, ensuring internships and placement opportunities.
Our Learning Facilitators
Meet our experienced and dedicated department team
Dr. Rajesh Kumar
Head of Department
Ph.D. in Data Science & ML
Dr. Priya Shankar
Associate Professor
Ph.D. in Artificial Intelligence
Mr. Arun Prakash
Assistant Professor
M.Tech in Big Data Analytics
Ms. Kavitha Raman
Assistant Professor
M.Sc CS, Data Science Specialist
Dr. Rajesh Kumar
Head of Department
Ph.D. in Data Science & ML
Dr. Priya Shankar
Associate Professor
Ph.D. in Artificial Intelligence
Mr. Arun Prakash
Assistant Professor
M.Tech in Big Data Analytics
Ms. Kavitha Raman
Assistant Professor
M.Sc CS, Data Science Specialist
Dr. Rajesh Kumar
Head of Department
Ph.D. in Data Science & ML
Dr. Priya Shankar
Associate Professor
Ph.D. in Artificial Intelligence
Mr. Arun Prakash
Assistant Professor
M.Tech in Big Data Analytics
Ms. Kavitha Raman
Assistant Professor
M.Sc CS, Data Science Specialist
Dr. Rajesh Kumar
Head of Department
Ph.D. in Data Science & ML
Dr. Priya Shankar
Associate Professor
Ph.D. in Artificial Intelligence
Mr. Arun Prakash
Assistant Professor
M.Tech in Big Data Analytics
Ms. Kavitha Raman
Assistant Professor
M.Sc CS, Data Science Specialist
Frequently Asked Questions
Find answers to common queries about the M.Sc Data Analytics programme
Begin Your Journey in Data Science
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