MCA (Master of Computer Applications) Generative AI- NVIDIA

Duration2 Years

View Curriculum Details

Course Fee3 Lakhs

View Fee Structure

MCA (Master of Computer Applications) Generative AI- NVIDIA

The MCA in Generative AI programme is designed to equip students with advanced knowledge and practical skills in artificial intelligence, focusing on generative models such as large language models, diffusion models, and neural networks.

The programme integrates core computer science concepts with cutting-edge AI technologies to prepare graduates for innovation-driven roles in industry and research.

 
Program Specific Outcomes (PSO)
PSO 01

To develop the technological planning and development of software applications in the usage of modern era.

PSO 02

To demonstrate the ability to simulate, analyze, design and deploy the software systems in advanced level for the industry and academic research.

Apply Now
Programme Outcomes (PO)

Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

vertical-line

Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

vertical-line

Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

vertical-line

Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

vertical-line

Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.

vertical-line

Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

vertical-line

Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

vertical-line

Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

vertical-line

Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

vertical-line

Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

vertical-line

Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

vertical-line

Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

vertical-line
Apply Now

Curriculum Details

Course Code Course Title C
CAP1005/CAP1005L Programming and Problem Solving using C 4
CAP4103/CAP4103L Data Structures and Applications 4
CAP4708 Computer Organization and Architecture 3
CAP4102/CAP4102L Advanced Database Management
Systems/Advanced Database Management
Systems Lab
4
Introduction to Generative AI 2
CAP4008/CAP4008L Software Engineering /Software Engineering Lab 3
Total Credits 20

Course Code Course Title C
MAT2003/MAT2003L Probability and Statistics using Python 4
CAP4005/CAP4005L Computer Networks and Security Essentials 4
Deep Learning Foundations 3
CAP4009/CAP4009L Java Programming 4
GMT2761 Principles of Management 2
Generative Models & Architectures 4
Total Credits 21

Course Code Course Title C
CAP5006/CAP5006L Operating System 4
CAP5707 Datawarehousing and Data Mining 3
CAP5007/CAP5007L Cloud Computing 4
Large Language Models 3
Departmental elective -2 3
Prompt Engineering & RAG 4
CAP4601 Minor Project 5
Total Credits 26

Course Code Course Title C
CAP4502 Major Project 18
Total Credits 18

Course Code Course Title C
CAP4707 Introduction to Social Network Analysis 3
CSE2721 Image Processing 3
CAP4704 Big Data Technologies 3
CAP5706 Artificial Neural Networks and Deep Learning 3
CAP5705 Cryptography and Network Security 3
CSE3803 Introduction to Data Science 3
Quantum Computing 3
CSE3704 Software Testing Methodologies 3
CAP4705 E-Commerce 3
Apply Now

Career Path

career-path

Graduates can pursue roles such as Generative AI Engineer, developing AI systems that create text, images, and code; Machine Learning Engineer, building and optimizing scalable ML models; and AI Research Associate, contributing to advanced AI research and innovation. Career opportunities also include NLP Engineer, focusing on language-based AI solutions, Data Scientist, deriving insights from complex datasets, and AI Product Developer, designing and delivering AI-powered products aligned with business needs.

Fee Structure

Yearly
1st Year 2nd Year
₹1,65,000 ₹1,35,000
Semester Wise
1st Sem 2nd Sem 3rd Sem 4th Sem
₹97,500 ₹67,500 ₹67,500 ₹67,500

Admission Requirement

Passed BCA/ Bachelor Degree in Computer Science Engineering or equivalent Degree. OR Passed B.Sc./ B.Com./ B.A. with Mathematics at 10+2 Level or at Graduation Level (with additional bridge Courses as per the norms of the University). Obtained at least 50% marks in the qualifying examination.

Apply Now
Admission Enquiry