Bachelor of Computer Applications (BCA) Artificial Intelligence Course, eligibility, Syllabus, Fees

Bachelor of Computer Applications (BCA) Artificial Intelligence Course, eligibility, Syllabus, Fees
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BCA (Artificial Intelligence)
Bachelor of Computer Applications
(Artificial Intelligence)
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Bachelor of Computer Applications
(Artificial Intelligence)
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About M.Tech Artificial Intelligence & Machine Learning
About
BCA (Artificial Intelligence)
The Bachelor of Computer Applications (BCA) Artificial Intelligence at Bennett University nurtures the next generation of students with the potential to revolutionise the AI landscape through rigorous training in fundamental research and application. The program focuses on both theoretical and practical applications of AI, preparing students to leverage the latest developments and technology to address pressing issues across diverse fields. The curriculum is interdisciplinary and innovation-driven, equipping students with the skills for high-demand roles like Data Scientist and Machine Learning Engineer. Key domains where students apply their knowledge include Agri-tech, Digital Healthcare, Fintech, Robotics, Media, and Environment Sustainability. The program includes a 20% research-focused component, such as industry certifications and projects with societal impact, ensuring students are industry-ready upon graduation.
Duration
3 Years/4 Years (Hons. /Hons. with Research)
Specialisations
14
Credits
120 (3-Year)
160 (4-Year)
Start Date
August 2026
Eligibility Criteria
Indian National:
Passed XII standard from any recognized Education Board with minimum 60% marks (Class XII Best of 3 subjects score) and English as compulsory subject
OR
IB Board with minimum score of 24 credits, 3 Higher level and 3 standard level subjects.
Bridge program for Physics/ Maths etc will be done by school
.
NRI:
Pass with 55% aggrigate marks in grade 12th/ A level or equivalent and English language requirement (ELR)
*Third subject should not be vocational: Music, Dance, Painting, Home Science, Arts, etc.
Selection Process
Selection will be based on merit of Class XII Best of 3 subjects score (comprising of English and Maths as compulsory subjects and any other third* subject with highest score)
*Third subject should not be vocational: Music, Dance, Painting, Home Science, Arts, etc.
BCA (Artificial Intelligence) Program Fee
Get detailed information about the BCA (Artificial Intelligence) program fee structure, including tuition, hostel fee, and other applicable charges
Click here for details.
Why BCA (Artificial Intelligence) from Bennett University
Our program is designed to equip students with the necessary knowledge and tools to excel in the rapidly evolving field of Artificial Intelligence.
Comprehensive Knowledge:
The program equips students with comprehensive knowledge of the foundational mathematical and computational aspects of AI.
Practical & Innovation-Driven:
Involves practical learning with state-of-the-art AI tools, technologies, and projects. Fosters an innovation-driven environment through Hackathons and AI Competitions.
Interdisciplinary Focus:
Promotes interdisciplinary research and provides a comprehensive understanding of real-world challenges.
Industry Relevance:
Curriculum is tailored to meet the industry’s demands and prepares students for a successful career.
Specialisations
The program emphasises an interdisciplinary approach with a focus on core AI/ML subjects. Students also have the option to choose from the following specialisations.
Digital Healthcare:
Students gain expertise in applying AI to clinical decision support, medical imaging, and patient-centric healthcare systems.
AgriTech:
Focuses on leveraging AI and machine learning for precision farming, crop monitoring, yield prediction, and sustainable agriculture.
Data Science:
Emphasis on advanced analytical and modelling skills to extract insights from structured and unstructured datasets.
Robotics:
Enables students to design and build intelligent autonomous systems with capabilities in perception, control, and real-time decision-making.
FinTech:
Students explore AI-driven financial technologies, including automated decision systems, risk modelling, and digital financial services.
MediaTech:
Develops an understanding of AI-enabled content intelligence, personalised recommendations, and audience analytics in digital media.
LegalTech:
Students gain exposure to NLP-based tools that automate legal research, contract analysis, and document review processes.
Quantum Information Processing:
Explores the intersection of AI and quantum mechanics to build next-generation algorithms and computational frameworks.
Environment & Sustainability:
Focuses on applying AI for climate modelling, pollution monitoring, and smart resource management to promote sustainable development.
Signal Processing:
Students learn core techniques for analysing and interpreting audio, image, and sensor signals for advanced AI applications.
Next-Generation Networks:
Enables students to apply AI/ML for designing, optimising, and securing future communication systems, including 5G and 6G networks.
Program Objectives
To train students in the foundational mathematical and computational aspects of AI and empower them to develop and apply intelligent systems. The program aims to cultivate strong analytical skills, problem-solving abilities, and creativity to tackle real-world challenges through research and practical projects.
Learning Outcomes
Upon completing the BCA in AI, students will be able to:
Develop Responsible AI:
Possess a deeper understanding of the mathematical and statistical aspects that form the fundamental pillars of Artificial Intelligence to develop responsible AI frameworks.
Master AI Concepts:
Master essential AI concepts, including Machine Learning, Inference Engines, Speech Recognition, Computer Vision, Natural Language Understanding, Robotics, and Human-Computer Interaction.
Design Systems:
Integrate human cognition, AI, and data engineering knowledge to design holistic systems.
Drive Research:
Possess an understanding of fundamental aspects of AI to drive research towards next-generation AI tools.
Build Robust Applications:
Develop real-time, robust AI-based systems tailored to specific software, hardware, and data constraints.
Curriculum Details
The curriculum is designed with a meticulous and interdisciplinary approach with a focus on core AI/ML subjects. By taking a holistic approach, it covers not only the technical aspects but also the practical applications of AI technologies. Students also have the option to choose minor options in diverse areas, which is part of the curriculum's structure. The BCA (Artificial Intelligence) curriculum follows the NEP 2020 guidelines with multiple entry/exit options and a credit framework.
Core Subjects:
Programming in Python and C++, Machine Learning & Deep Learning Algorithms, Cyber Security, Cloud, Data Structures, Computer Vision, LLMs, Generative AI & others.
Specialisation Options:
Digital Healthcare, AgriTech, Data Science, Robotics, FinTech, MediaTech, LeagalTech, Quantum Information Processing, Environment & Sustainability, Signal Processing, Next Generation Networks & others.
Research Component:
20% research-focused coursework, including industry certifications and projects.
Career Pathways
Graduates of the BCA (Artificial Intelligence) program are highly sought after across diverse industries such as Information Technology, Fin-tech, Gaming, and Virtual Reality (VR). They can pursue dynamic and rewarding career roles, including Data Scientist, Machine Learning Engineer, AI Researcher, AI Consultant, Big Data Analyst and Natural Language Processing (NLP) Engineer, among others.
Faculty
Prof. (Dr.) Rajeev Tiwari
Dean, School of Artificial Intelligence
Dr. Manoj Sharma
Ph.D. - IIT Delhi
Dr. Pratyush Pranav
Ph.D. - University of Groningen
Dr. Dinesh Kumar
Ph.D. - University of Coimbra, Portugal
Dr. Shakshi Sharma
Ph.D. - University of Tartu, Estonia
Dr. Neelam Choudhary
Ph.D. - IIT Guwahati
Dr. Navneet Pratap Singh
Ph.D. - IIT Indore
Dr. Yajnaseni Dash
Ph.D. - IIT Delhi
Dr. Gaurav Sharma
Ph.D. - NIT, Hamirpur
Dr. Prateek Yadav
Ph.D.- IIT Delhi
OUR ASK
BCA (Artificial Intelligence) Program
Frequently Asked Questions
What is the course curriculum of the BCA (Artificial Intelligence) program?
The curriculum balances theoretical research and practical applications, with an interdisciplinary approach and minor options. It includes a 20% research-focused component, like industry certifications and projects with societal impact. It aligns with NEP 2020, offering multiple entry/exit options and various credit categories.
What are the career prospects after completing BCA AI?
There is high demand across IT, Finance, Gaming, and VR industries. Roles include Data Scientist, Machine Learning Engineer, AI Researcher, etc.
What are the skills required to excel in the BCA AI program?
Strong analytical skills, problem-solving, critical thinking, and creativity are essential. Proficiency in Python, C++, machine learning algorithms, data structures, and computer vision is also beneficial.
Is it necessary to have a background in Computer Science to pursue BCA in Artificial Intelligence?
It is not necessary, but foundational knowledge in programming, algorithms, and data structures will be beneficial.
What is the difference between BCA (Artificial Intelligence) and BCA Computer Science?
BCA (AI) focuses on intelligent agents (e.g., machine learning, robotics, NLP), while BCA (CS) covers broader topics like software development, database systems, networking, and computer architecture.
Are there hands-on projects and industry certifications integrated into the course?
Yes, the curriculum involves practical learning with state-of-the-art AI tools, Hackathons, and includes a 20% research-focused component for industry certifications and projects.
Does the BCA (Artificial Intelligence) program include a research component?
Yes, the program has a 20% research-focused component that includes industry certifications and projects with societal impact.
Which programming languages are taught in the first year?
Foundational programming is typically taught in the first year, including languages like C/C++ and Python, which are crucial for AI and Machine Learning applications.
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