This three-year (or four-year Honours variant, as per NEP guidelines) undergraduate program in Bachelor of Computer Applications with a specialization in Artificial Intelligence (AI) and Machine Learning (ML) blends foundational computer applications education with cutting-edge training in intelligent technologies.
Programme at a Glance
This three-year (or four-year Honours variant, as per NEP guidelines) undergraduate program in Bachelor of Computer Applications with a specialization in Artificial Intelligence (AI) and Machine Learning (ML) blends foundational computer applications education with cutting-edge training in intelligent technologies.
It equips students with core computing skills in programming, data structures, databases, software development, web technologies, and networking, while providing in-depth specialization in AI/ML concepts such as supervised and unsupervised learning, deep learning, neural networks, natural language processing (NLP), computer vision, generative AI, reinforcement learning, data analytics, big data tools, and ethical AI practices.
Through a balanced mix of theoretical coursework, hands-on labs using tools like Python, TensorFlow, PyTorch, scikit-learn, and cloud platforms, real-world projects, internships, capstone developments, and industry collaborations, students learn to design, build, deploy, and optimize AI-powered applications and intelligent systems that solve complex problems in sectors like healthcare diagnostics, predictive analytics, recommendation engines, autonomous systems, chatbots, fraud detection, and more, preparing them for the demands of the rapidly growing AI-driven digital economy.
AI-First Curriculum
Deep learning, NLP, computer vision, reinforcement learning, and generative AI from Year 3 onwards.
Industry-Integrated Learning
Mandatory internship + real-world capstone project with industry mentors.
Research Opportunities
GPU-powered AI Research Lab access. Co-author papers with faculty from Year 3 onwards.
Global Certifications
Embedded AWS, Google Cloud, NVIDIA, and TensorFlow Developer certifications within the curriculum.
Four core aims that define what this programme sets out to achieve for every student.
01
Expert Knowledge in AI & CS
Build a solid foundation in computer applications and programming while delivering specialized expertise in AI and ML technologies.
02
Ethical AI Professionals
Develop competent professionals capable of creating intelligent, data-driven solutions and automated systems.
03
Research, Innovation & Leadership
Prepare students for entry-level roles in the tech industry, advanced studies, research, and innovation in emerging AI domains.
04
Industry 4.0 / 5.0 Readiness
Align skills with Industry 4.0/5.0 requirements, including modern tools, ethical considerations, and practical application development.
Four core aims that define what this programme sets out to achieve for every student.
Provide comprehensive knowledge in core computer applications alongside advanced AI/ML topics like machine learning algorithms, deep learning architectures, and data processing.
Train students in key techniques including NLP, computer vision, predictive modeling, and model deployment strategies.
Enhance analytical thinking, programming proficiency, and problem-solving abilities for data-intensive and intelligent computing challenges.
Offer practical exposure through projects, labs, internships, hackathons, and industry case studies to bridge theory and practice.
Foster innovation, ethical AI awareness, teamwork, entrepreneurship, and lifelong learning in a dynamic technological landscape.
Enable graduates to pursue global careers, higher education (MCA/M.Tech/M.Sc. in AI/ML), or research contributions.
Eight measurable outcomes that every graduate of this programme will demonstrate.
PO1
Technical Proficiency
Apply knowledge of computer applications, mathematics, statistics, AI, and ML to solve real-world computing problems.
PO2
Problem Analysis & Intelligent Solutions
Identify, analyze, and formulate AI/ML-based approaches to complex problems using data-driven techniques and algorithms.
PO3
System Design & Development
Design, implement, train, evaluate, and deploy AI/ML models and applications with focus on accuracy, scalability, and efficiency.
PO4
Modern Tool Usage
Effectively use contemporary tools, languages, and frameworks (e.g., Python, TensorFlow, PyTorch, scikit-learn, Pandas, cloud ML services) for development, experimentation, and production.
PO5
Research & Innovation
Explore emerging AI/ML trends, conduct basic research, innovate solutions, and evaluate models critically for improvement.
PO6
Teamwork & Communication
Collaborate in teams, manage AI projects, and communicate technical insights, results, and documentation effectively.
PO7
Ethics & Sustainability
Understand ethical, legal, and societal implications of AI, promote fairness, bias mitigation, privacy, and responsible use in intelligent systems.
PO8
Lifelong Learning
Adapt to evolving AI technologies, tools, and paradigms through continuous self-learning and professional development.
Graduates are equipped for the most exciting and high-growth roles in the AI & tech
industry.
Design and deploy production-grade ML models and intelligent systems at scale.
Extract insights from complex datasets using statistical modelling and advanced analytics.
Conduct cutting-edge research in deep learning, NLP, or CV at top research labs worldwide.
Build language models, translation systems, and intelligent dialogue agents.
Build image recognition, object detection, and video analytics systems for real-world deployment.
Guide enterprises in adopting intelligent systems and AI-driven transformation strategies.
Manage model lifecycle, CI/CD pipelines, and scalable AI infrastructure on cloud platforms.
Work with LLMs, diffusion models, and multimodal AI for creative and enterprise applications.