UGC Recognized Postgraduate Programme

Master of Science in Computer Science

Specialization in Data Analytics & Machine Learning

2 Years Duration
4 Semesters
Full-Time Programme
NAAC

Accredited Institution

Quality assured education

12:1

Learner-Facilitator Ratio

Personalized mentorship

95%+

Placement Record

Industry-ready graduates

₹8L

Average Package

Data science roles

About the Programme

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.

Industry-Aligned Curriculum
Expert Learning Facilitators
GPU-Powered Lab Infrastructure
Industry Internship Programme
Data Analytics LabSince 1952
Admissions

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
Curriculum

Programme Curriculum

Comprehensive syllabus designed to build expertise in data analytics and machine learning

Semester I

  • Advanced Data Structures & Algorithms
  • Statistical Methods for Data Analytics
  • Python for Data Science
  • Database Management Systems
  • Practical: Python & Statistics Lab
  • Research Methodology

Semester II

  • Machine Learning Fundamentals
  • Big Data Technologies
  • Data Visualization & Business Intelligence
  • R Programming for Analytics
  • Practical: ML & Big Data Lab
  • Soft Skills & Professional Communication
Outcomes

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.

Careers

Career Opportunities

Diverse career pathways await M.Sc Data Analytics graduates

Data Scientist

Build predictive models and derive insights at tech giants

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

Information TechnologyBanking & FinanceHealthcare & PharmaE-commerce & RetailConsulting FirmsTelecommunicationsInsurance & ActuarialManufacturing & Supply ChainMedia & EntertainmentGovernment & Public SectorResearch & AcademiaStartups & Unicorns
Infrastructure

Department Facilities

State-of-the-art infrastructure supporting world-class data science education

High-Performance Computing Lab

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

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

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

Enterprise Software Suite

Licensed access to Tableau, Power BI, SAS, SPSS, MATLAB, and industry-standard analytics tools for comprehensive learning experience.

Research & Innovation Center

Research & Innovation Center

Dedicated space for dissertation work, industry collaborations, and research projects with mentorship from industry experts and Learning Facilitators.

Digital Library & E-Resources

Digital Library & E-Resources

Access to IEEE Xplore, ACM Digital Library, Springer, and Coursera/edX subscriptions for continuous learning beyond the curriculum.

Campus Life at JKKN
Why Us

Why Choose Our M.Sc Computer Science Programme?

Our progressive education approach ensures holistic development, preparing you for success in data science and AI careers.

Expert Learning Facilitators

Learn from PhD-qualified Learning Facilitators with industry experience at companies like Google, Microsoft, and Amazon.

Hands-on Practical Learning

60% practical curriculum with real-world datasets, Kaggle competitions, and capstone projects on live business problems.

Industry Partnerships

Collaborations with TCS, Infosys, Wipro, and startups for guest lectures, internships, and placement opportunities.

Mandatory Internship Programme

6-month industry internship with leading companies to gain real-world experience before graduation.

Exceptional Placement Support

Dedicated placement cell with 95%+ placement record and average packages of ₹6-8 LPA for data science roles.

Faculty

Our Learning Facilitators

Meet our experienced and dedicated department team

Dr. Rajesh Kumar

Dr. Rajesh Kumar

Head of Department

Ph.D. in Computer Science (AI/ML)

Dr. Priya Lakshmi

Dr. Priya Lakshmi

Associate Professor

Ph.D. in Data Science

Mr. Venkatesh Babu

Mr. Venkatesh Babu

Assistant Professor

M.Tech, NET Qualified

Ms. Anjali Sharma

Ms. Anjali Sharma

Assistant Professor

M.Sc CS, SLET Qualified

Dr. Rajesh Kumar

Dr. Rajesh Kumar

Head of Department

Ph.D. in Computer Science (AI/ML)

Dr. Priya Lakshmi

Dr. Priya Lakshmi

Associate Professor

Ph.D. in Data Science

Mr. Venkatesh Babu

Mr. Venkatesh Babu

Assistant Professor

M.Tech, NET Qualified

Ms. Anjali Sharma

Ms. Anjali Sharma

Assistant Professor

M.Sc CS, SLET Qualified

Dr. Rajesh Kumar

Dr. Rajesh Kumar

Head of Department

Ph.D. in Computer Science (AI/ML)

Dr. Priya Lakshmi

Dr. Priya Lakshmi

Associate Professor

Ph.D. in Data Science

Mr. Venkatesh Babu

Mr. Venkatesh Babu

Assistant Professor

M.Tech, NET Qualified

Ms. Anjali Sharma

Ms. Anjali Sharma

Assistant Professor

M.Sc CS, SLET Qualified

Dr. Rajesh Kumar

Dr. Rajesh Kumar

Head of Department

Ph.D. in Computer Science (AI/ML)

Dr. Priya Lakshmi

Dr. Priya Lakshmi

Associate Professor

Ph.D. in Data Science

Mr. Venkatesh Babu

Mr. Venkatesh Babu

Assistant Professor

M.Tech, NET Qualified

Ms. Anjali Sharma

Ms. Anjali Sharma

Assistant Professor

M.Sc CS, SLET Qualified

FAQ

Frequently Asked Questions

Find answers to common queries about the M.Sc Computer Science (Data Analytics) programme

The M.Sc Computer Science (Data Analytics) programme is a 2-year full-time postgraduate degree comprising four semesters. The first three semesters focus on coursework combining theoretical concepts with practical lab sessions, while the fourth semester is dedicated to industry internship and dissertation work. Each semester includes core subjects, practical labs, and elective courses.
After completing M.Sc Computer Science (Data Analytics), Learners can pursue Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or Data Science from prestigious universities globally. Additional options include specialized MBA programmes in Business Analytics, post-doctoral research positions, and executive education programmes from institutions like IIMs, ISB, and international universities.
The programme provides comprehensive training in Python (primary language), R, SQL, and exposure to Scala. Learners gain proficiency in libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, and Keras. Big data tools include Hadoop, Spark, and Kafka. Visualization tools covered include Tableau, Power BI, and D3.js. Cloud platforms AWS, Azure, and GCP are integrated throughout the curriculum.
While prior programming experience is beneficial, it is not mandatory. The programme begins with foundational courses in Python and data structures. However, candidates should have strong mathematical aptitude, particularly in statistics and linear algebra. A background in computer science, mathematics, or statistics is highly recommended. Bridge courses are available for Learners from non-CS backgrounds.
Our M.Sc Data Analytics programme boasts a 95%+ placement record. Entry-level packages range from ₹4.5 to ₹8 lakhs per annum for Data Analyst roles. Machine Learning Engineers and Data Scientists command packages of ₹8-15 lakhs. Top performers have secured positions at companies like TCS, Infosys, Wipro, Accenture, and tech startups with packages exceeding ₹12 lakhs. The highest package recorded was ₹18 LPA.
Yes, the programme includes preparation for industry-recognized certifications at no additional cost. Learners are trained for AWS Certified Data Analytics, Microsoft Azure Data Scientist Associate, Google Cloud Professional Data Engineer, and Tableau Desktop Specialist certifications. The department conducts mock exams and provides study materials to ensure Learners are well-prepared for these valuable certifications.
The mandatory industry internship in the fourth semester spans 4-6 months. The placement cell facilitates internships at partner companies including IT majors, consulting firms, and data-driven startups. Learners work on real business problems, applying their data science skills under industry mentor guidance. Many internships convert to pre-placement offers (PPOs), giving Learners a head start in their careers.
Enroll Now

Launch Your Career in Data Science

Join our M.Sc Computer Science (Data Analytics) programme and transform into a skilled data professional ready for the AI-driven future.