M.Sc. Information Technology in Data Science

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The M.Sc. Information Technology in Data Science at CMR University’s School of Science and Computer Studies (SSCS) is a two-year postgraduate programme designed to provide in-depth expertise in data science, analytics, and computational intelligence. This programme equips students with strong theoretical foundations and practical skills to analyse, interpret, and derive insights from complex datasets, preparing them for high-demand roles in data-driven industries.

The curriculum is structured to cover core concepts in statistics, machine learning, big data analytics, artificial intelligence, data visualisation, and cloud computing. Students gain hands-on experience with programming languages such as Python, R, and SQL, along with data tools like TensorFlow, Hadoop, and Tableau. The programme integrates real-world case studies, industry projects, and internships, ensuring that students develop problem-solving skills and technical expertise aligned with industry needs.

With data becoming the backbone of decision-making, this programme prepares graduates for roles such as Data Scientists, Machine Learning Engineers, Business Analysts, AI Specialists, and Big Data Engineers in industries such as finance, healthcare, retail, e-commerce, and IT services. The programme also provides a solid foundation for students interested in pursuing research, doctoral studies, or advanced certifications in data science and artificial intelligence.

To enhance employability, the programme includes soft skills training, technical workshops, and pre-placement guidance, enabling students to excel in the competitive job market. SSCS at CMR University also fosters collaborations with industry leaders, research institutions, and startups, providing students with exposure to emerging trends and innovations in data science.

With state-of-the-art labs, expert faculty, and a research-driven learning environment, the M.Sc. Information Technology in Data Science at CMR University empowers students to become pioneers in the evolving world of data and analytics.

Duration

2 years

Programme Fees

Rs. 45,000/- per semester

Programme Type

Full-time

Programme Regulations

2024-25

Eligibility Criteria

Candidates should have passed with a minimum of 50% marks (45% in case of SC/ST candidates) in B.Sc. – Computer Science / BCA / B.Sc. – IT / B.Sc. – CT or an equivalent examination from a recognised university, preferably with Mathematics at the 10+2 level or at the graduation level.

Scope and Objective

An M.Sc. in IT with a specialisation in Data Science prepares graduates for high-level careers in data science, analytics, and machine learning. The programme covers advanced topics such as deep learning, big data technologies, statistical modelling, and artificial intelligence. Graduates can pursue careers as Data Scientists, Machine Learning Engineers, or Data Consultants in industries such as finance, healthcare, e-commerce, and telecommunications.

The programme also equips students with research skills, enabling them to contribute to cutting-edge innovations in data science. With the growing reliance on data-driven strategies across industries, the demand for data science professionals is expected to rise. Graduates may also pursue doctoral studies or certifications in specialised areas such as AI or data engineering.

To offer in-depth knowledge of advanced data science techniques, including machine learning, deep learning, and big data technologies.
To provide practical experience in managing large datasets and deriving insights using tools like Hadoop, Spark, and TensorFlow.
To develop the ability to apply data science methodologies to solve complex problems in various industries, including finance, healthcare, and retail.
To prepare graduates for high-level roles as Data Scientists, Machine Learning Engineers, and Data Consultants.
To cultivate research skills, enabling students to contribute to innovations in data science and AI.
To prepare students for further academic research (Ph.D.) or advanced certifications in areas such as AI, data engineering, or specialised fields of data science.
To promote teamwork, communication, and project management skills by engaging students in collaborative projects and internships.

Programme Structure

Semester I

Advanced Database Management Systems and Lab
Python and R Programming and Lab
Research Methodology and IPR
Probability and Statistics
Elective 1 :
- Computer Networks and Security
- Distributed Computing
Elective 2:
- Advanced Algorithms
- Object-Oriented Modeling and Design
Community Service – I
Common Core Courses

Semester II

Artificial Intelligence and Lab
Internet of Things and Lab
Introduction to Data Science
Software Project Management
Elective 3:
- Advanced Optimization Techniques
- Multivariate Data Analysis
Elective 4:
- Introduction to Augmented Reality and Virtual Reality
- Data Mining
Interdisciplinary Elective I
Common Core Courses
Community Service – II

Semester III

Machine Learning using Python and Lab
Data Visualization using PowerBI and Tableau and Lab
Advanced Cloud Computing
Soft Computing Techniques
Elective 5:
- Natural Language Processing Techniques
- Digital Marketing And Web Analytics
- Predictive Analytics
Elective 6:
- Blockchain Technology
- Digital Forensics
MOOC
Interdisciplinary Elective II
Internship
Common Core Courses

Semester IV

Big Data Analytics using Hadoop
Elective 7:
- Deep Learning
- Digital Image Processing
Elective 8:
- Cloud Security
- Wireless Sensor Networks
Capstone Project

Programme Assessment

Choice-Based Credit System (CBCS): CMR University follows CBCS, allowing students to choose courses and earn credits based on their performance.
Grades and GPA: Students are awarded grades for each course in a semester. SGPA is calculated to measure academic performance per semester, and CGPA evaluates overall performance across semesters.
Prescribed Curriculum: Each programme includes a Scheme of Teaching and Evaluation, incorporating required courses, laboratories, and degree requirements. It also includes MOOCs offered by reputed institutions through platforms like SWAYAM.
Auditing Courses: Students may audit courses to gain additional exposure without the pressure of grading. This may benefit students during placements.
Evaluation System: Evaluation is continuous and consists of Continuous Internal Evaluation (CIE) and Semester End Examination (SEE), each contributing 50% to the final grade.
Assessment Methods: Faculty may employ various methods, including assignments, seminars, group discussions, case studies, industry reports, quizzes, and presentations.
Semester End Examination: SEE is conducted for all registered courses at the end of each semester. Some courses may not require SEE if sufficient CIE is conducted.
Makeup Examinations: Students failing in SEE are eligible for makeup examinations to improve their grades.

Programme Outcome

PO1: Develop the ability to analyse problems, and identify and define computing requirements appropriate to their solutions.
PO2: Apply knowledge of mathematics and science fundamentals to develop solutions for complex problems.
PO3: Apply analytical methods to interpret and analyse results obtained from experiments, drawing appropriate conclusions.
PO4: Demonstrate soft skills and values to function effectively as individuals and as members or leaders in diverse teams and multidisciplinary settings.
PO5: Apply mathematical and experimental methods to study advanced concepts and principles across various branches of science.

Course Outcomes Visit

What expertise will you gain?

Advanced programming skills in languages such as Java, C#, or Python
Knowledge of software engineering principles and methodologies
Proficiency in database management systems and SQL
Understanding of computer networks and cybersecurity
Project management and software development lifecycle skills

Career Opportunities

01
Software Developer
02
Database Administrator
03
Systems Analyst
04
Software Engineer
05
IT Project Manager
06
Mobile Application Developer

How to apply?

Eligibility Criteria

A Bachelor’s degree in Computer Science, IT, Mathematics, or a related field from a recognised university.

Application Process

Visit the official website of CMR University and navigate to the Admissions section.
Website: www.cmr.edu.in
Fill out the online application form with personal, academic, and contact details.
Upload the necessary documents, including mark sheets, ID proof, and passport-size photographs.
Pay the application fee online.

Selection Process

Applications are reviewed based on academic performance and eligibility criteria.
Some programmes may require students to appear for an entrance test and/or personal interview.
Shortlisted candidates will receive an admission offer letter via email.

Confirmation of Admission

Once selected, candidates must confirm their admission by paying the first instalment of the tuition fee within the stipulated time.
Students must submit the original documents for verification at the university campus.

Orientation & Enrolment

Upon successful admission, students will be invited for an orientation programme, where they will receive details about course structure, academic guidelines, campus facilities, and student support services.

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