BCA / BCA (H)

(with specialization in Machine Learning) in Association with Microsoft

BCA / BCA (H)

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.

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

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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.

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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.

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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.

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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.

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

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

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

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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.

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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.

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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.

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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

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

01

Complete the Application

02

Appear for Entrance test and interview

03

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.

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