Postgraduate Programme
Master of Science in Data Science
School of Sciences

Master of Science in Data Science
- Duration 2 Years
- Semester 4
Total Fee: 2,50,000 INR
Overview
Data Science is popular in all academia, business sectors, and research and development to make effective decisions in day-to-day activities. The Master of Data Science (MDS) is a postgraduate program that combines computer science and statistics to foster proficiency in data-driven decision-making. It is a two-year course comprising four semesters.
This programme aims to provide opportunity to all candidates to master the skill sets specific to data science with research bent. The curriculum supports the students to obtain adequate knowledge in theory of data science with hands-on experience in relevant domains and tools. Candidates gain exposure to research models and industry standard applications in data science through guest lectures, seminars, projects, etc.
Syllabus
Fees
M.Sc (Data Science)
Programme Fee: INR 2,50,000
Application Fees: INR 1,500 + GST (Non-refundable)
Admission Process Fees: INR 5,000 (Non-refundable)
Examination Fees: INR 3,000 per year
*Flexible EMI options are available for tuition fee payments. Choose a convenient installment plan at checkout to manage your fees with ease.
Cancellation Policy
Application Process
Candidates are required to apply online only through the University website www.christuniversity.in. No other means/mode of application will be accepted.
Step-1: Register as a New Applicant
Register once to apply for multiple programs with the same ID.
- Fill in your details: Enter your name (as per class 10 certificate), email, phone numbers, date of birth, and password. Verify your details before submitting. Click 'Register' to complete.
- Verify with OTP: You will receive an OTP on your mobile and email. Enter the OTP and click 'Proceed'. Check the spam folder if the email is not in your inbox.
Step-2: Procedure to Login
- Login with your credentials: Use your registered email ID and password to log in. Enter them correctly in the respective fields.
- Click on the Login button: After entering your details, click on the 'Login' button.
- Forgot password: If you forgot your password, click on the 'Forgot Password' button and follow the necessary steps to reset it.
Step-3: Fill Personal Information
- Select the program and campus to which you want to apply. Ensure all data is correct before proceeding, as it cannot be edited later.
- Upload a formal photo (3.5 cm x 4.5 cm with white background, max 100 kb). Photos with other backgrounds or taken with mobile devices will result in rejection.
- Fill in personal, educational, and parent/guardian details. Upload clear scanned copies of class 10 and class 11 final report or class 12 Board result.
- Preview and ensure the accuracy of all information before submitting.
- Select the date and centre for the selection process. Refer to the Important Dates section before making a selection.
Step-4: Application Fee Payment
- Payment Methods: Net Banking, Credit Card, Debit Card, or UPI.
- Non-Refundable: The application fee is non-refundable once the application number is generated.
- Payment Failure: In case of payment failure, the amount will be refunded within 15 business days.
- Printing the Application: A copy of the application can be printed anytime until the selection process is completed.
Why choose this course?
- Curriculum blends theory, hands-on experience, and research focus.
- Gain expertise in data science tools for real-world problem-solving.
- Extensive electives, projects, and industry exposure enhance employability.
- Inculcate rigorous problem-solving skills.
- Fosters ethical practices, teamwork, and continuous learning mindset.
- Develops the ability to function effectively both individually and in diverse teams.
What you will learn?
- Application- based learning using tools like Python, R, SQL, Tableau, Hadoop, Advanced Excel
- Master problem analysis, design, and data science principles
- Acquire proficiency in programming tools for domain-specific problem-solving.
- Apply data science theories to address societal and environmental concerns.
- Embrace professional ethics, fostering research culture and scientific integrity.
- Develop individual and teamwork skills in diverse, multidisciplinary environments.
- Engage in continuous reflective learning, adapting to evolving data paradigms.
Career prospects
- Earn advanced certifications (eg AWS, Azure, Google Data Certifications)
- Pursue leadership roles or entrepreneurial ventures in technical and data domains.
- Career Opportunities: Data Scientist,Data Analyst,Machine Learning Engineer,AI/Deep Learning Specialist,Big Data Engineer,Business Intelligence Analyst,Data Architect,Research and Academic Opportunities,Leadership and Consulting Roles ( Data Science Consultant, Data-Centric Project Manager, Chief Data Officer)
Admission Queries
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