BCA Generative Artificial Intelligence
Bachelor of Computer Applications (Honours / Honours with Research)
Generative AI (GUVI-HCL Partnered)
Overview
The Bachelor of Computer Applications (Honours / Honours with Research) with Major in Generative Artificial Intelligence is a future-focused undergraduate programme designed to build strong computational foundations alongside deep, applied expertise in modern AI systems. Positioned among leading generative AI courses in India, the programme offers a rigorous academic structure that integrates core computer science disciplines—programming, data structures, databases, networking, and operating systems—with advanced Generative AI domains including machine learning, deep learning, natural language processing, large language models, and contemporary generative architectures.
The BCA Generative AI syllabus is carefully structured to balance theoretical depth with applied learning, ensuring students develop both conceptual clarity and technical competence. Emphasis is placed on experiential and project-centric learning, enabling students to translate academic knowledge into deployable, AI-driven solutions. Through laboratories, internships, industry-mentored projects, and transdisciplinary learning models, learners are trained to design, develop, and evaluate intelligent systems addressing real-world and industry-relevant challenges.
As one of the emerging generative AI courses in Bengaluru, the programme benefits from proximity to India’s leading technology and innovation ecosystem, offering students enhanced exposure to industry practices, research environments, and entrepreneurial networks. Clear articulation of generative AI course eligibility ensures accessibility for students from diverse academic backgrounds, while progressive exit options aligned with NEP 2020 support flexible academic pathways.
Ethical AI, responsible data usage, and the societal implications of intelligent systems are embedded throughout the curriculum, reinforcing the programme’s academic and social relevance. Through its comprehensive design, industry alignment, and research orientation, the programme contributes to the growing recognition of JAIN (Deemed-to-be University) among the top generative AI course colleges in India and the best generative AI course colleges in India, preparing graduates for leadership roles, advanced research, and innovation-driven careers in artificial intelligence.
Duration: 4 Years - 8 Semesters
Total Credits: 172
Eligibility
Course Highlights
- GEN AI–focused curriculum emphasising experiential learning, peer learning, and hands-on activities at a leading undergraduate Computer Science institution.
- Distinctive industry interaction opportunities through tailored industry visits, collaborations, workshops, value-added programs, and AI-focused research, providing real-world connections beyond typical academia.
- Additionally, the curriculum offers in-depth learning in data management, networking, software systems, and AI technologies, aligned with Generative AI applications.
- Moreover, academic and practical guidance is provided by highly experienced faculty with strong expertise in both AI research and industry practices.
- In addition, entrepreneurship and innovation training help develop problem-solving skills, business acumen, and confidence to build AI-driven startups and solutions.
- An extended learning initiative enabling students to explore AI tools, build models, and work on real-world projects beyond regular classroom hours.
- 100DaysOfCode - This connects social accountability with continuous learning. Students post daily learning milestones, creating a digital record of progress.
- Product/Project Exhibition – Offers hands-on learning experiences that transform knowledge into innovation.
- 6AMClub – Industry mentors will connect with students at 6 AM.
- Pitch Day - Encourages creativity and innovation among students.
Study Campus
JAIN Knowledge Campus
# 44/4, District Fund Road
Jayanagar 9th Block Campus
Bangalore - 560 069
080 - 69279444
+91 83109 42174
Admissions Office
JAIN Knowledge Campus
# 44/4, District Fund Road
Jayanagar 9th Block Campus
Bangalore - 560 069
080 - 69279444
+91 83109 42174
Curriculum Structure
- Mathematical foundation for AI and Data Analytics
- Problem Solving Techniques using C
- Computer Organization
- Professional Communication Skill - I
- Languages 1
- Kannada-1
- Hindi-1
- Sanskrit-1
- Additional English-1
- Problem Solving Techniques using C Lab
- Computer Organization Lab
- Disaster Management and Preparedness
- Mind Management and Human Values 1
- Transdisciplinary Project Centric Learning 1
- Data Structures Using C
- Advanced Mathematical methods For Computer Science
- Object Oriented Programming using Java-Swayam integrated
- Professional Communication Skill - II
- Language-II
- Kannada-II
- Hindi-II
- Sanskrit-II
- Additional English-II
- Data Structures Using C Lab
- Object Oriented Programming using Java Lab
- Open Elective-1
- Mind Management and Human Values 2
- Transdisciplinary Project Centric Learning 2
- Database Management Systems
- Computer Networks
- Problem Solving using Python
- Prompt Engineering
- Minor-1
- Open Elective-2
- Indian Constitution
- Database Management Systems Lab
- Problem Solving using Python Lab
- Summer Internship 1 (6 to 8 Weeks)
- Transdisciplinary Project Centric Learning 3
- Operating System
- Minor - 2
- Minor - 3
- Elective Group:
- Generative Models : GANs, VAEs, Diffusion Models
- Open Elective - 3
- Environmental Studies(Swayam)
- Minor - 2 Lab
- Minor - 3 Lab
- Transdisciplinary Project Centric Learning 4
Track 1 (Conventional Approach)
- Foundations of Machine Learning and Deep Learning for Generative AI
- Elective Group
- Building GenAI Application
- Building LLM Models
- Retrieval Augmented Generation ( RAG ) System
- Artificial Intelligence(AI)
- Building GenAI applications
- Building LLM Models
- Retrieval augmented generation ( RAG ) system
- Artificial Intelligence lab
- Minor - 4
- Minor - 5
- Summer internship 2 (6 to 8 week)
- Transdisciplinary Project Centric Learning 5
- Minor project
Track 2 (Capstone Project Approach)
- Building Gen AI Applications
- Minor - 4
- Minor - 5
- Minor - 4 Lab
- Minor - 5 Lab
- Summer internship 2 (6 to 8 week)
- Transdisciplinary Project Centric Learning 5
Track 3 (Entrepreneurship)
- Entrepreneurship
- Building Gen AI Applications
- Minor - 4
- Minor -5
- Minor - 4 Lab
- Minor -5 Lab
- Summer Internship 2 (6 to 8 week)
- Transdisciplinary Project Centric Learning 5
Track 1: (Conventional Approach)
- Elective Group
- Advanced Techniques and Applications of Generative AI
- Gen AI Architecture
- Generative AI for Business & Industry Use-cases
- Advanced Techniques and Applications of Generative AI
- Advanced Techniques and Applications of Generative AI lab
- Gen AI Architecture lab
- Minor - 6 Integrated with Swyam
- Major Project
- Seminar
- Transdisciplinary Project Centric Learning 6
Track 2: (Capstone Project Approach)
- Capstone Project
- DSC: Generative AI for Business Innovation & Product Development
- Minor - 6- Integrated with Swayam
- Seminar
- Transdisciplinary Project Centric Learning 6
Track 3: (Entrepreneurship)
- Entrepreneurship
- DSC -Generative AI for Business Innovation & Product Development
- Minor - 6 Integrated With Swayam
- Transdisciplinary Project Centric Learning 6
- Seminar
- DSE-1
- DSC-2
- Minor - 7
- Industry Mentored Project
- Summer Internship-3
- DSC-1
- DSC-1
- Minor - 7
- Research Methodology
- Applied Research
- Summer Internship-3
- DSC-1
- DSC-2
- Minor - 8
- Industry Mentored Project
- Summer Internship-4
- Dissertation (For Research Track)
- Minor - 8
- Software Engineering
- Cloud Computing
- Internet of Things (IoT)
- Information Technology for Health Care (ITH)
- Information Security (IS)
Career Outcomes
Graduates of the BCA (Honours / Honours with Research) program with a Major in Generative AI (GUVI–HCL Partnered) pursue diverse, evolving professional roles, including:
Foundational AI and Software Development Practice
Graduates start by building, testing, and maintaining intelligent software that combines programming logic with foundational AI. They use skills in Python, data handling, and algorithms to support AI in various domains. As Junior AI Engineers, AI Trainees, Software Developers, Data Analysts, or AI Support Engineers, they help with decision-making, evaluate models, and maintain applications. They also develop professional discipline, collaboration, and ethical awareness of AI.
Applied AI Engineering and Intelligent Application Development
As they grow, graduates design and launch AI-powered apps that link machine learning models to user needs. They work through the development lifecycle: data preparation, model integration, API use, and system deployment. Often, this is in cloud or enterprise settings. As AI Application Developers, Machine Learning Associates, Full Stack Developers (AI), and Automation Engineers, they turn AI concepts into scalable solutions that improve efficiency, user experience, and intelligence. They focus on responsible automation and explainable AI.
Advanced Generative AI, Data Science, and Specialised Intelligence Systems
With more experience, graduates build advanced AI systems, including Generative AI models, NLP pipelines, and predictive analytics frameworks. They focus on model optimisation, large-language-model workflows, and data-driven problem-solving. These professionals—AI Engineers, Data Scientists, Generative AI Developers, and NLP Engineers—combine maths, domain expertise, and ethics to create robust and responsible systems.
AI Architecture, Technical Leadership, and Strategic Solutions
At senior levels, graduates direct AI adoption and system design in organisations. They lead teams, build scalable AI ecosystems, and match technical solutions with business and social goals. As Senior AI Engineers, AI Solutions Architects, or Technical Leads (AI), they manage governance, MLOps, security, and sustainability. Their work blends technology, strategy, and leadership, so AI innovation is accountable, inclusive, and aligns with values.
Research, Innovation, and Entrepreneurial Pathways
Graduates interested in research or entrepreneurship expand the limits of AI knowledge and use. They pursue advanced studies or research as Research Associates, or progress to MSc, MCA, MS, or PhD programmes. They contribute to academic inquiry, applied research, and policy innovation. Some start ventures as AI Startup Founders or work as AI Consultants, turning Generative AI skills into solutions for real-world problems. These paths emphasise innovation, ethics, and long-term impact over short-term trends.
Together, these paths show the program’s focus on adaptability, ethics, and lifelong learning. Graduates remain relevant and resilient as Generative AI technologies, roles, and social expectations change.
Career Enhancement
To strengthen employability and research readiness, the programme integrates structured career enhancement initiatives, including:
- Generative AI Certification Programmes in Prompt Engineering, Machine Learning, LLMs, and applied AI tools.
- Industry Internships and Live Projects focused on automation, chatbots, intelligent systems, and AI product development.
- AI Skill Bootcamps and Workshops covering Python for AI, data handling, model development, and AI toolchains.
- Hackathons, Ideathons, and Coding Challenges to cultivate innovation, teamwork, and problem-solving capabilities.
- Cloud and AI Deployment Training, introducing cloud platforms and foundational MLOps concepts.
- Entrepreneurship and Startup Development Programmes supporting AI-based venture creation and innovation pipelines.
- Soft Skills and Employability Training encompassing communication, professional ethics, aptitude, and interview readiness.
- Research and Innovation Exposure through mini research projects, incubation labs, and applied AI research practices.
- Extended and Night AI Labs, enabling deeper experimentation beyond formal classroom hours.
FAQ's
What is the focus of the BCA GEN AI programme?
The programme focuses on building a strong foundation in computer science along with specialised skills in Generative Artificial Intelligence, including machine learning, deep learning, NLP, and AI-driven application development.
Do students need prior programming knowledge?
No. Foundational programming and computer science are taught from the first semester.
What career opportunities can students expect after completing the programme?
Graduates can work as Junior AI Engineers, Data Analysts, AI Developers, or pursue further studies or research in AI.
Are there hands-on learning and industry exposure opportunities?
Yes. Labs, projects, internships, and collaborations provide hands-on and industry exposure.