• To produce competent professionals in Artificial Intelligence and Machine Learning through excellence in education and move the society in interesting and innovative directions

• To Provide technical knowledge on par with Industry to the students through qualified faculty members having knowledge in recent trends and technologies.
• To transform the students into technically proficient professionals in the field of Artificial Intelligence and Machine learning.
• To Provide opportunities for students to improve leadership skills in order to address a variety of societal concerns through team work and innovative projects.

Students graduating from Computer Science and Engineering (Artificial Intelligence and Machine Learning) should be able to:

• PO1: Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex Artificial Intelligence and Machine Learning problems.
• PO2: Problem Analysis: Identify, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and Artificial Intelligence and Machine Learning.
• PO3: Design/Development of Solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations in the field of Artificial Intelligence and Machine Learning.
• PO4: Conduct Investigations of Complex Problems: Using research-based knowledge and Artificial Intelligence & Machine Learning oriented research methodologies including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
• PO5: Modern Tool Usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex Artificial Intelligence and machine learning engineering activities with an understanding of the limitations.
• PO6: The Engineer and Society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
• PO7: Environment and Sustainability: Understand the impact of the professional Artificial Intelligence and Machine Learning Engineering solutions in societal and environmental contexts, and demonstrate the knowledge, and need for the sustainable development.
• PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
• PO9: Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams and in multidisciplinary settings.
• PO10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
• PO11: Project Management and Finance: Demonstrate knowledge and understanding of the Artificial Intelligence and Machine Learning engineering and management principles and apply these to one’s own work, as a member and leader in a team and, to manage projects in multidisciplinary environments.
• PO12: Lifelong Learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Graduates of Computer Science Engineering (Artificial Intelligence and Machine Learning) Programme should be able to:

• PSO1: Apply fundamental concepts of Artificial Intelligence and Machine Learning according to excellence and excitement towards research, to provide elegant solutions to complex problems.
• PSO2: Develop skills to address and solve Artificial Intelligence based social and automate business solutions using cutting edge technologies.

Graduates of Computer Science Engineering (Artificial Intelligence and Machine Learning) Programme should be able to:

• PEO1: Graduates will be able to apply their technical knowledge to solve real world problems, with adequate leadership qualities.
• PEO2: Graduates will have the capability to apply their knowledge and skills to identify the cutting edging research and develop the solutions on problems of social relevance.
• PEO3: Graduates will be able to engage in life-long learning by completing advanced software Technologies, certificates, and/or other professional development.

Computer Science and Engineering (AI & ML) is a forward-looking specialization designed to meet the growing technological demands of intelligent systems and automation across various industries.

• Focus on Core AI & ML Technologies: The program offers in-depth exposure to Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, and Reinforcement Learning.
• Cutting-Edge Infrastructure: Equipped with high-performance computing labs and AI-specific resources to facilitate hands-on learning and innovation.
• Industry-Driven Curriculum: Designed in collaboration with industry experts, the curriculum includes advanced topics like Explainable AI, Predictive Analytics, Edge AI, Computer Vision, and Ethical AI.
• Real-World Project Exposure: Encourages students to work on live projects, case studies, and capstone projects in collaboration with industry and research organizations.
• Skill-Oriented Learning: Prepares students with essential skills in programming, data modelling, algorithmic thinking, and decision-making under uncertainty.
• Experiential Learning Opportunities: Through internships, hackathons, coding competitions, and collaborative research with leading tech companies and academic institutions.
• Career Readiness: Trains students for high-impact roles such as Machine Learning Engineer, AI Research Scientist, AI Software Developer, NLP Engineer, Robotics Engineer, and Computer Vision Specialist, AI/ML Consultant, Entrepreneur / AI Start-up Founder
• Interdisciplinary Applications: Opens opportunities in diverse sectors including Healthcare, Finance, Automotive, Agriculture, Cybersecurity, Education, and Smart Manufacturing.
• Global Collaborations: Offers access to certification programs, MOOCs, and exchange opportunities with reputed universities in India and abroad.
• Start-up and Innovation Ecosystem: Encourages entrepreneurial thinking and innovation through incubation support, mentorship, and funding opportunities.

• Intel Unnati AI (High Performance Computing) Laboratory
• Advanced Computing Laboratory in collaboration with C-DAC
• Machine Learning Laboratory
• Data Science Laboratory
• Data Structures Laboratory
• Database Management and Systems Laboratory
• Deep Learning Laboratory
• Big data analytics Laboratory
• Data Visualization Laboratory

• AICTE-Juniper Networks AI Driven Campus
• National Cyber Security Research Council in Cyber Security & Artificial Intelligence
• NXDEEP CONNECTZ software solutions, Coimbatore
• Thedush Robotics, Coimbatore

• CSI (Computer Society of India)
• ISTE (Indian Society for Technical Education)
• IEEE

• Coursera (Exclusive Login)
• Altair (Data Engineering)
• Infosys Spring Board

Regulation

R-2023 UG

Curriculum & Syllabi

R-2023