BCA / BCA (H)
(with specialization in Machine Learning) in Association with Microsoft
Duration4 Years
Machine learning is an emerging technology which enables computers to learn automatically from past data. It uses various algorithms for building mathematical models and making predictions using historical data or information.
Currently, it is being used for various tasks such as image recognition, speech recognition, email filtering, Facebook auto-tagging, recommender system, and many more. BCA in ML is a specialized program to cater to huge demand in IT and Machine Learning.
Program Specific Outcomes (PSO)
PSO 01
To learn the concepts of Computer Science and Applications such as Operating System, Computer Networks, Computer Organisation and Architecture, DBMS and Data Structures which meet the desired needs of industry and society.
PSO 02
To analyze their abilities in systematic planning, developing, testing and executing complex computing applications in field of Social Media and Analytics, Web Application Development and Data Interpretations, Machine Learning and Data Analytics for providing solutions to computational problems.
PSO 03
Graduates would expertise in successful careers based on their understanding of formal and practical methods.
Programme Outcomes (PO)
To apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
To identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
To 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.
T 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.
To create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
To 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.
To understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
To apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
To function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
To 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.
To 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.
To 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.
Curriculum Details
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| MAT1705 | Basic Mathematics | 3 | 1 | 0 | 4 |
| CAP1005/CAP1005L | Problem solving and programming through C | 3 | 0 | 2 | 4 |
| CAP1004/CAP1004L | Introduction to IT | 3 | 0 | 2 | 4 |
| VAC001 | Design Thinking | 2 | 0 | 0 | 2 |
| COM1515 | Modern English Language | 2 | 0 | 0 | 2 |
| CAI1012 | Machine Learning Industry vertical | 2 | 0 | 0 | 2 |
| FIN1799 | Basics of Financial Management | 3 | 0 | 0 | 3 |
| CAP1502L | PC Software Lab/Engineering Workshop | 0 | 0 | 2 | 1 |
| Total Credits | 22 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CAP2702 | Computer System Architecture | 3 | 0 | 0 | 3 |
| CAI1009/CAI1009L | Mathematics for Machine Learning (2L and 2P) | 2 | 0 | 2 | 3 |
| CAP2007/CAP2007L | Principles of Operating Systems | 3 | 0 | 2 | 4 |
| CAP2001/CAP2001L | Data Structure using C | 3 | 0 | 2 | 4 |
| LAW3702 | Constitution Of India | 3 | 0 | 0 | 3 |
| COM1521 | Communication Skills and Ability Enhancement | 2 | 0 | 0 | 2 |
| VAC002 | Innovation, Entrepreneurship and Sustainability | 1 | 0 | 2 | 2 |
| Total Credits | 21 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CAP2017/CAP2017L | Introduction to Object Oriented Concepts Using Java | 3 | 0 | 2 | 4 |
| CAP2002/CAP2002L | Introduction to Database Management Systems | 3 | 0 | 2 | 4 |
| CAI1008/CAI1008L | IDP1 | 2 | 0 | 2 | 3 |
| CAP3004/CAP3004L | Artificial Intelligence | 3 | 0 | 0 | 3 |
| CAP2018/CAP2018 | Design and Analysis of Algorithm | 2 | 0 | 2 | 3 |
| HUM2790 | Essense of Indian Traditional Knowledge | 3 | 0 | 0 | 3 |
| COM2521 | Academic Writing | 2 | 0 | 0 | 2 |
| Total Credits | 22 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CAP2005/ CAP2005L | Software Engineering Fundamentals | 3 | 0 | 0 | 3 |
| From Maths | Discrete Mathematical Structures through Python | 3 | 0 | 2 | 4 |
| ITL 1001 | Computer Networks | 2 | 0 | 2 | 3 |
| CAI1007 | Basics of Machine Learning | 2 | 0 | 0 | 2 |
| CAI1010/CAI1010L | IDP2 | 3 | 0 | 0 | 3 |
| COM2525 | Work Place Communication | 2 | 0 | 0 | 2 |
| ENV1702 | Environmental Studies | 3 | 0 | 0 | 3 |
| Total Credits | 20 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CAP3702 | Theory of Computation | 3 | 1 | 0 | 4 |
| CAP3012/CAP3012 | Data Warehousing and Data Mining | 3 | 0 | 2 | 4 |
| DE1 | Departmental Elective-I | 3 | 0 | 0 | 3 |
| CAP2016 | Full Stack Development | 3 | 0 | 2 | 4 |
| CAP3703 | Research Methodology | 2 | 0 | 0 | 2 |
| CAI1011/CAI1011L | Implementing AI Solution on Microsoft Azure | 2 | 0 | 4 | 4 |
| Total Credits | 21 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CAP3013/CAP3013L | ANN | 3 | 0 | 2 | 4 |
| DE-2 | Departmental Elective-II | 3 | 0 | 0 | 3 |
| CAP3701 | Cloud Computing | 3 | 0 | 2 | 4 |
| DE-3 | Departmental Elective-III | 3 | 0 | 0 | 3 |
| CAP3014/CAP3014L | Natural Language Processing | 3 | 0 | 2 | 4 |
| Total Credits | 18 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CAP 4014/CAP 4014L | Deep Learning | 3 | 0 | 2 | 4 |
| CAP3804 | Optimization Techniques | 3 | 0 | 0 | 3 |
| CAP4015/CAP4015 | Cryptography and Network Security | 3 | 0 | 2 | 4 |
| CAP2015/CAP2015L | Data Visualization using R | 2 | 0 | 2 | 3 |
| Summer Internship | Summer Internship | 0 | 0 | 0 | 3 |
| CAP4503 | Project Phase 1 | 3 | 0 | 0 | 3 |
| Total Credits | 20 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CAP3702 | Social Network Analysis | 3 | 0 | 0 | 3 |
| Departmental Elective-4 | Departmental Elective-4 | 3 | 0 | 0 | 3 |
| CAP 4504 | Project Phase 2 | 0 | 0 | 0 | 10 |
| Total Credits | 16 | ||||
Career Path

- Artificial Intelligence / Machine Learning Developer
- Artificial Intelligence / Machine Learning Architect
- Research scientist
- Business Analyst
- Lead Artificial Intelligence / Machine Learning Engineer
- Data Scientist
- Data Analyst
- NLP Engineer.
Fee Structure
Yearly
| 1st Year | 2nd Year | 3rd Year | 4th Year |
|---|---|---|---|
| ₹2,10,000 | ₹1,70,000 | ₹1,70,000 | ₹1,70,000 |
Semester Wise
| 1st Sem | 2nd Sem | 3rd Sem | 4th Sem | 5th Sem | 6th Sem | 7th Sem | 8th Sem |
|---|---|---|---|---|---|---|---|
| ₹1,25,000 | ₹85,000 | ₹85,000 | ₹85,000 | ₹85,000 | ₹85,000 | ₹85,000 | ₹85,000 |
Admission Process
Complete the Application
Appear for Entrance test and interview
Get shortlisted and Received the offer letter
BCA / BCA (H) (with specialization in Machine Learning) in Association with Microsoft
Passed the XII standard from any recognized Education Board with a minimum of 50% marks and English as a compulsory subject.