The two-year Master of Computer Applications (MCA) in Artificial Intelligence and Data Science program focuses on the design and development of information systems, providing a robust foundation in Information Technology and Data Science. MCA students gain a deep understanding of the principles, concepts, and foundations of computer science, IT, and related applications, while also acquiring extensive programming and software development experience across a variety of platforms and applications. The curriculum includes explicitly defined lab components that integrate theoretical learning with hands-on implementation.
Students who successfully complete the program and meet the requirement of completing at least 5 out of 9 electives in the AI and Data Science stream will graduate with a specialization in AI and Data Science.
This specialization equips students with advanced knowledge and skills in Artificial Intelligence and Data Science, focusing on the use of cutting-edge technologies and analytical techniques to extract meaningful insights from large datasets and develop intelligent solutions for complex real-world problems.
Program Highlights
The MCA program offers a comprehensive curriculum that delves into advanced topics such as Artificial Intelligence and Data Science. It includes specialized courses in soft skills development, a wide range of elective options, and mandatory research-oriented courses, all designed to prepare students for diverse professional roles. This well-rounded approach ensures graduates are fully equipped to succeed in the ever-evolving field of information technology.
Graduates of the program are highly sought after and secure positions in prestigious multinational companies, often with competitive salary packages.
Career Opportunities
Amrita Vishwa Vidyapeetham has not appointed any Agent or Third-Party Client for securing admission in any programme. Students are hereby requested to contact only the toll-free number on our website for any admission related queries.
– Issued In Public Interest By Directorate Of Admissions And Academic Outreach
Passed any graduation degree (e.g.: B.E. / B.Tech./ B.Sc / B.Com. / B.A./ B. Voc./ BCA etc.,) preferably with Mathematics at 10+2 level or at Graduation level. Obtained at least 50% marks in the qualifying examination.
Selection will be based on merit and interview process.
2 Years- 4 Semester
Program Fee for the Year 2025-26 (Semester Wise)Tuition Fee: Rs. 60,500 Hostel Fee for the Year 2025-26 (Semester Wise)Hostel Fee: Rs. 13,750 |
| Sl. No. | Course Title | Theory / Practical | Credits |
| 1 | Object-Oriented Programming Using Java | T + P | 4 |
| 2 | Mathematical Foundations for Computer Applications | T | 4 |
| 3 | Data Structures | T + P | 4 |
| 4 | Advanced DBMS | T + P | 4 |
| 5 | Professional Elective I | T + P | 4 |
| 6 | Elective I | T | 3 |
| 7 | Mastery Over Mind | T | 2 |
| 8 | Glimpses of Indian Culture | T | P/F |
| 9 | Life Skills – 1 | T | 1 |
| Credits (A) | 26 |
| Sl. No. | Course Title | Theory / Practical | Credits |
| 1 | Design and Analysis of Algorithms | T | 4 |
| 2 | Software Engineering and Design Patterns | T | 4 |
| 3 | Problem Formulation and Research Tools | P | 1 |
| 4 | Professional Elective II | T + P | 4 |
| 5 | Professional Elective III | T + P | 4 |
| 6 | Elective II | T | 3 |
| 7 | Elective III | T | 3 |
| 8 | Open Lab I | P | 1 |
| 9 | Life Skills – II | T | 1 |
| Credits (B) | 25 |
| Sl. No. | Course Title | Theory / Practical | Credits |
| 1 | Professional Elective IV | T + P | 4 |
| 2 | Professional Elective V | T + P | 4 |
| 3 | Elective IV | T | 3 |
| 4 | Open Lab II | P | 1 |
| 5 | Open Lab III | P | 1 |
| 6 | Dissertation Phase I | 6 | |
| Credits (C) | 19 |
| Sl. No. | Course Title | Theory / Practical | Credits |
| 1 | Dissertation Phase II | 12 | |
| Credits (D) | 12 | ||
| Total Credits: 82 Credits | |||
| Sl. No. | Course Title |
| 1 | Data Modelling and Visualization |
| 2 | Exploratory Data Analysis |
| 3 | Data Mining and Applications |
| 4 | Machine Learning |
| 5 | Big Data Analytics |
| 6 | Natural Language Processing |
| 7 | NLP for Robotics |
| 8 | Large Language Models |
| 9 | Computer Vision |
| 10 | Knowledge Engineering |
| Sl. No. | Course Title |
| 1 | Deep Learning |
| 2 | Linear Algebra and Applications |
| 3 | Artificial Intelligence |
| 4 | Database Administration |
| 5 | Time Series Analysis |
| 6 | Information Retrieval |
| 7 | Information Science and Ethics |
| 8 | Pattern Recognition |
| 9 | Recommendation Systems |
| 10 | Web Mining |
| 11 | Business Analytics and Visualization |
| 12 | Computational Intelligence |
| Sl. No. | Course Title |
| 1 | Python Scripting for Security |
| 2 | Ethical Hacking Lab |
| 3 | Python Programming |
| 4 | C#.Net |
| 5 | Android Programming |
| 6 | UI/ UX design |
| 7 | Linux Programming |
| 8 | Competitive programming |
| 9 | Edge computing |
| 10 | R programming |
| 11 | MATLAB Programming |
| 12 | High-Performance computing |
| 13 | Cyber Security |
| 14 | Algorithms Lab |
| 15 | Deep Learning Lab |
| 16 | SQLite |
The top reasons to choose Amrita for your career
