Overview
Bachelor of Computer Application with Specialization in AI & Data Science is a three-year undergraduate programme brought in association with Samatrix and IBM, BCA in AI & Data Science focuses on deepest insights into the science of Big Data Analytics and how Artificial Intelligence is driving the growth. Students will receive both theoretical and practical knowledge in subjects like Java, Net Frameworking, Data Warehousing, Data Mining, Mobile Application Development & handling data.
Eligibility Criteria
Candidate must have passed 10+2 examination or equivalent in any stream with mathematics/IP and CS as one subject with minimum 50% aggregate marks.
Programme Details
Programme Highlights
Building exceptional understanding and expertise to turn ideas into solutions, the Bachelor’s in Computer Applications aims at ensuring rigorous pragmatic training and hands-on experience in working on advanced new-age systems and technologies.
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The curriculum is specifically designed in consultation with industry insiders and experts
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Realistic hands-on training for absolute excellence
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Globally accredited certification upon successful completion of the BCA with Specialization in AI and data science programme
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Consistent mentoring by acclaimed academicians and top industry experts
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Highly sophisticated laboratories equipped with cutting-edge tech apparatus
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Ensuring absolute preparedness for successful career progression
Programme Structure
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Semester 1 |
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Course Title |
Credit |
|
Web Designing Using HTML,CSS, Java Script & PHP
|
4 |
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Basics of Mathematics
|
4 |
|
Clean Coding with Python
|
4 |
|
Essentials of Software Engineering
|
4 |
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Web Design Lab
|
1 |
|
Clean Coding with Python Lab
|
1 |
|
Environmental Studies & Disaster Management (Online Moodle)
|
2 |
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Essentials of Software Engineering Lab
|
2 |
|
Data Visualization using Power BI
|
2 |
|
Semester 2 |
|
Course Title |
Credit |
|
Fundamentals of Object Oriented Programming using C++
|
4 |
|
Discrete Structure
|
4 |
|
Overview of AI, Data Science, Ethics and Foundation of Data Analysis
|
4 |
|
R Programming for Data Science and Data Analytics Lab
|
2 |
|
Object Oriented Programming Lab using C++
|
1 |
|
Overview of AI, Data Science, Ethics and Foundation of Data Analysis Lab
|
1 |
|
Open Elective -1
|
1 |
|
Extention Activities(community engagement service)
|
3 |
|
Semester 3 |
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Course Title |
Credit |
|
Fundamentals of Data Structures
|
4 |
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Fundamentals of Java Programming
|
4 |
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Probabilistic Modelling and Reasoning
|
2 |
|
Fundamentals of Artificial Intelligence
|
4 |
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Fundamentals of Java Programming Lab
|
1 |
|
Fundamentals of Data Structures Lab
|
1 |
|
Open Elective -II
|
3 |
|
VAC III
|
2 |
|
Life Skills for Professionals-I
|
3 |
|
Summer Internship/Project
|
2 |
|
Semester 4 |
|
Course Title |
Credit |
|
Fundamentals of Operating Systems |
4 |
|
Fundamentals of Database Management Systems |
4 |
|
Foundation of Machine Learning |
4 |
|
Fundamentals of Operating System Lab |
1 |
|
Foundation of Machine Learning Lab |
1 |
|
Fundamentals of Database Management Systems Lab |
1 |
|
Open Elective -III |
3 |
|
Life Skills for Professionals-II |
3 |
|
VAC IV |
2 |
|
Minor project-I |
2 |
|
Semester 5 |
|
Course Title |
Credit |
|
Design and Analysis of Algorithms
|
4 |
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Theory of Automata
|
4 |
|
Introduction to Natural Language Processing
|
4 |
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Big Data Analysis with Scala and Spark
|
4 |
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Data Science - Tools and Techniques Lab
|
2 |
|
Life Skills for Professionals-III
|
3 |
|
Design & Analysis of Algorithms Lab
|
1 |
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Natural Language Processing Lab
|
1 |
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Big Data Analysis with Scala and Spark Lab
|
1 |
|
Summer Internship /Project
|
2 |
|
Semester 6 |
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Course Title |
Credit |
|
Department Elective I
|
4 |
|
Introduction to Computer Organization & Architecture
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4 |
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Introduction to Computer Networks
|
4 |
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Basics of Neural Networks and Deep Learning
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4 |
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Department Elective I Lab
|
1 |
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Computer Networks Lab
|
1 |
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Neural Networks and Deep Learning Lab
|
1 |
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Competitive Coding
|
2 |
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Minor Project-II
|
2 |
Programme Outcomes
Engineering Graduates will be able to:
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PO1. Fundamental Knowledge: Demonstrate a strong foundation in computer science principles, mathematics, and fundamental concepts necessary for the understanding and application of computing.
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PO2. Problem Solving: Apply analytical and critical thinking skills to identify, analyze, and solve complex computing problems using appropriate tools, algorithms, and programming languages.
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PO3. Software Development: Design, develop, and implement software solutions by applying software engineering principles, programming languages, and best practices.
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PO4. Database Management: Design, implement, and manage databases, ensuring efficient data storage, retrieval, and manipulation using database management systems.
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PO5. Web Technology: Develop web-based applications and utilize relevant technologies, frameworks, and tools for effective web development and deployment.
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PO6. Network and Security: Understand network protocols, security mechanisms, and implement secure network configurations to ensure data integrity, confidentiality, and availability.
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PO7. Information Management: Gather, organize, and analyze information from various sources using appropriate technologies and tools for effective decision-making and problem-solving.
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PO8. Team Collaboration: Collaborate effectively as a member or leader in multidisciplinary teams, demonstrating effective communication, interpersonal skills, and adaptability to work in diverse professional environments.
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PO9. Ethical and Professional Practices: Adhere to ethical, legal, and professional standards in computing, recognizing the social and ethical responsibilities associated with the use of technology.
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PO10. Lifelong Learning: Recognize the need for continuous learning, keep up-to-date with emerging trends in technology, and engage in self-directed learning to adapt to evolving computing paradigms.
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PO11. Industry Relevance: Apply industry-relevant practices, tools, and technologies to bridge the gap between academia and industry, ensuring the ability to meet industry requirements and contribute effectively to the computing field.
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PO12. Entrepreneurial Mindset: Identify opportunities, demonstrate innovation, and apply entrepreneurial thinking to create value, solve problems, and contribute to the growth of businesses and society.
Programme Educational Objectives (PEOs)
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PEO1 - Develop expertise in AI and Data Science through research-oriented learning and gain the ability to apply advanced concepts in practical settings.
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PEO2 - Pursue a successful career in AI and Data Science by applying knowledge and skills to industry-related problems or further academic pursuits.
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PEO3 -Engage in lifelong learning and develop innovative solutions in the domain of AI and Data Science using research and problem-solving skills to contribute to the sustainable development of society.
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PEO4 - Demonstrate leadership, teamwork, management, ethical and social responsibility, and communication skills with a commitment to lifelong learning.
Programme Specific Outcomes (PSOs)
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PSO1 - Demonstrate a strong foundation in the theoretical concepts and practical applications of AI and Data Science, including machine learning, data analysis, and data visualization.
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PSO2 - Develop critical thinking, problem-solving, and research skills through hands-on projects, independent study, and engagement in research activities related to AI and Data Science.
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PSO3 - Apply knowledge and skills to solve industry-related problems through internships, capstone projects, and experiential learning opportunities in collaboration with industry partners.
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PSO4 - Demonstrate leadership, teamwork, management, ethical and social responsibility, and communication skills by engaging in team-based projects, leadership activities, and community outreach initiatives related to AI and Data Science.
Who should Pursue
Students who are interested in the use of modern technologies, the IT sector, and data science and are keen learners who want to have a career as a software developer or engineer should opt for BCA in AI and Data Science programme.
Financial Assistance
K.R. Mangalam University partnered with the leading banks to help you to finance your dream course through Education Loan. You only have to start repaying one year after finishing your course or six months after you get a job.
Benefits:
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Quick and Instant
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Includes tuition fees, books cost, hostel fees, airfare.
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Concessional rate of interest.
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Speedy disposal of loan applications
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Availability of the loan across the country
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Up to 100% loan with lower interest rate and zero processing fees
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Repayment tenure ranging from 5-15 years.
Career Options
Students who graduate from BCA with specialization in Artificial Intelligence and Data Science will have the opportunity to go into various job profiles such as
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Software Engineer
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Business Analyst
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Data Scientist
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Digital Marketer
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CyberSecurity Experts
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Go for MCA
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Software Developer
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Blockchain Professional
Placements
K.R. Mangalam University aims at making students industry-ready with a regular curriculum and academic placements. KRMU has joined hands with well-respected companies like IBM, Punjab National Bank, Flipkart, Axis Bank, Microsoft, Bank of Baroda and many other top recruiters.
Faq
Yes, K.R. Mangalam University extends promising financial assistance in partnership with major banks and firms including GrayQuest, ICICI Bank, IDFC FIRST Bank, and Axis Bank.
Some of the top recruiters offering leading roles to BCA (AI & Data Science) graduates are IBM, Punjab National Bank, Flipkart, Axis Bank, Microsoft, Bank of Baroda, and HCL.
The total fee for BCA in AI & Data Science programme is INR 1,75,000/- which is to be paid semester-wise. The fee for Semester I is INR 75,000/- and for Semester II is INR 70,000/-
Yes, the students inclined to pursue the BCA (AI & Data Science) programme may be eligible for the scholarship in accordance with the terms and conditions.
The students seeking admission to BCA (AI & Data Science) are required to fill out the Online Application Form and take the KREE Entrance Assessment Test. Upon successful clearance, the shortlisted students have to attend the Faculty-Led Interview for confirmed successful enrolment.
Some of the key study areas covered in the BCA (AI & Data Science) curriculum includes Basics of Mathematics, Object Oriented Programming, Web Technologies, Data Structures, Java Programming, Computer Organization & Architecture, and Database Management Systems.