The B.Tech in Computer Science & Engineering with specialization in Artificial Intelligence & Machine Learning is designed to develop skilled professionals and innovators in the rapidly evolving fields of AI and ML.
Programme at a Glance
About the Programme
The B.Tech in Computer Science & Engineering with specialization in Artificial Intelligence & Machine Learning is designed to develop skilled professionals and innovators in the rapidly evolving fields of AI and ML.
The program provides a strong foundation in core computer science along with specialized knowledge in intelligent systems, data-driven technologies, and advanced computational methods. Students gain expertise in areas such as machine learning, deep learning, natural language processing, computer vision, generative AI, reinforcement learning, and ethical AI practices.
Through practical learning, industry exposure, projects, internships, and research-oriented activities, the program prepares graduates for emerging opportunities in Industry 4.0 and digital transformation.
AI-First Curriculum
Deep learning, NLP, computer vision, reinforcement learning, and generative AI integrated throughout the programme.
Industry-Focused Learning
Strong industry exposure through internships, live projects, hackathons, and capstone projects.
Industry-Integrated Training
Real-world learning with practical applications, mentorship, and hands-on experience in emerging AI technologies.
Research Opportunities
Access to AI research labs, innovation projects, and opportunities to work on research-oriented applications.
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
Deliver robust foundational and advanced knowledge in Computer Science, AI, and ML to foster expertise in intelligent system design and deployment.
02
Ethical AI Professionals
Cultivate professionals skilled in creating autonomous, adaptive, and ethical AI-driven solutions for real-world challenges across industries.
03
Research, Innovation & Leadership
Prepare students for pioneering research, technological innovation, entrepreneurial ventures, and leadership roles in academia and industry.
04
Industry 4.0 / 5.0 Readiness
Equip graduates with contemporary tools, frameworks, and methodologies aligned with emerging global standards in AI and Industry 4.0/5.0.
Four core aims that define what this programme sets out to achieve for every student.
Impart comprehensive knowledge in core computer science, mathematics, and advanced AI/ML concepts.
Train students in state-of-the-art techniques including machine learning, deep
learning, NLP, computer vision, reinforcement learning, and generative models.
Develop strong analytical, problem-solving, programming, and system-design skills for complex, data-intensive problems.
Provide extensive practical exposure via projects, internships, hackathons, research collaborations, and real-world applications.
Foster innovation, entrepreneurship, interdisciplinary thinking, ethical awareness, and commitment to lifelong learning.
Position graduates for advanced research, global careers, and contributions to sustainable, inclusive technological advancement.
Eight measurable outcomes that every graduate of this programme will demonstrate.
PO1
Technical Proficiency
Apply in-depth knowledge of mathematics, computer science, AI, and ML to solve complex real-world engineering problems.
PO2
Problem Analysis & Intelligent Solutions
Identify, formulate, analyze, and design AI/ML-based solutions using modern algorithms and data-driven approaches.
PO3
System Design & Development
Design, develop, deploy, and optimize scalable AI/ML systems, pipelines, and applications with considerations for performance, security, and maintainability.
PO4
Modern Tool Usage
Proficiently use contemporary tools, languages, and platforms — Python, TensorFlow, PyTorch, scikit-learn, cloud ML services, MLOps frameworks — for model building and production deployment.
PO5
Research & Innovation
Conduct independent research, innovate in emerging AI/ML domains, and contribute novel solutions through experimentation and critical evaluation.
PO6
Teamwork & Communication
Collaborate effectively in multidisciplinary teams and communicate technical ideas clearly to diverse audiences.
PO7
Ethics & Sustainability
Apply professional ethics, understand societal/environmental impacts, and promote responsible, fair, and inclusive AI practices.
PO8
Lifelong Learning
Adapt to rapidly evolving technologies, pursue continuous self-improvement, and engage in lifelong 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.