Christ University

What you'll study

The programme mixes core subjects, specialisation electives and capstone work. Semester 1 is described as Foundations of Statistics, Programming and Data Engineering. Core modules named in the curriculum include:

• Statistical Methods
• Programming using Python
• Visual Analytics
• Prescriptive and Operational Models
• Data Engineering & Data Pipelines
• Statistical Learning Models
• Statistical NLP & NLG
• Data Driven Decision Science
• Applied AI in Business
• IoT and Cloud Analytics

Students select a specialisation track—Data Science and Analytics; Data Engineering and Big Data; or Applied Artificial Intelligence—and take specialised electives such as deep learning models and real-time data modeling. Capstone projects are integrated across semesters to apply learning to real-world problems.

Entry requirements

The published page refers to an eligibility criteria and a fee structure but does not list specific academic or professional entry conditions in the provided text. Prospective applicants should consult the programme admissions page or contact the university for exact eligibility rules and application steps.

Career prospects

The degree targets roles across analytics, AI and engineering. Early-semester outcomes include positions such as Data Analyst, Junior Data Analyst, Reporting Analyst, Business Analytics Associate and Data Visualization Analyst. Later-semester and specialisation outcomes listed include Data Scientist, BI Analyst, Big Data Analyst, Analytics Consultant, Machine Learning Analyst and Decision Science Associate. The Data Science and Analytics track reports an average starting package cited as ₹ 8-15 LPA.

Scholarships & funding angle (general)

The source does not specify scholarships. Working professionals may benefit from employer sponsorship given the weekend schedule and industry orientation; applicants should enquire with the university about scholarships, fee concessions, instalment plans or external funding options available for postgraduate programmes.