Computer Science & Engineering (Artificial Intelligence & Machine Learning)

Document

Dr. Ranjith K C BE, M.Tech, PhD, MISTE

Asscoiate Professor and Head

Department of Computer Science & Engineering (Artificial Intelligence & Machine Learning)

Vission and Mision

Vision

To achieve excellent standards of quality education in the field of Artificial intelligence and Machine Learning.

Mission

To nurture the students with strong fundamentals for a successful carrier in the field of artificial intelligence and machine learning.

To motivate the students for post-graduation and research.

To create impact in the society with continuous research and innovations.

Department Activities

Department Intake

Academic Year	Sanctioned Intake		Admitted Students
	Regular	Lateral	Regular	Lateral
2025-2026	60+3		63
2024-2025	60+3	6	63	6
2023-2024	60+3	6	63	6

ABOUT THE DEPARTMENT

As the Head of the Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning) at Maharaja Institute of Technology Mysore, it is my privilege to welcome you to our newly established department. Founded in 2023 with an intake of 60 students, we are committed to establishing ourselves as a leader in AI education, bridging the gap between traditional computer science and the rapidly evolving field of artificial intelligence. Our curriculum is thoughtfully designed to provide a strong foundation in both computer science and AIML, with an emphasis on practical applications alongside theoretical knowledge in areas such as machine learning, natural language processing, computer vision, and robotics. As a young and dynamic department, we are uniquely positioned to adapt swiftly to the latest advancements in AI. Our mission is to develop not just skilled engineers, but visionary problem-solvers capable of addressing complex challenges through AI-driven solutions. Despite being newly established, we are actively building partnerships with industry leaders and research institutions to provide our students with cutting-edge learning experiences and opportunities. We invite you to join us on this exciting journey as we explore the vast possibilities of artificial intelligence and shape the next generation of AI innovators and leaders.

Program Educational Objectives

PEO1 Acquire fundamentals and expertise in data engineering skills for professional career in industry, government, academia as innovative engineers.

PEO2 Pursue higher studies with research potential.

PEO3 Demonstrate professional ethics and attitude as an individual or team member at workplace and function professionally in a global competent world.

Program Outcomes

PO1: Engineering Knowledge: Apply knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO2: Problem Analysis: Identify, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO3: Design/Development of Solutions: Design solutions for complex engineering problems and design system components or processes that meet specified needs with appropriate consideration for public health, safety, cultural, societal, and environmental considerations.

PO4: Conduct Investigations of Complex Problems: Use research-based knowledge and research methods, including design of experiments, analysis and interpretation of data, and synthesis of 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 engineering activities.

PO6: The Engineer and Society: Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal, and cultural issues and the consequent responsibilities relevant to professional engineering practice.

PO7: Environment and Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts, demonstrating knowledge of and need for sustainable development.

PO8: Ethics: Apply ethical principles, commit to professional ethics, responsibilities, and norms of engineering practice, including inclusive practice and equity.

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 society at large, such as being able to comprehend and write effective reports, design documentation, and make effective presentations.

PO11: Project Management and Finance: Demonstrate knowledge and understanding of engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects in multidisciplinary environments.

Program Specific Outcomes

PSO1: Software Systems: Apply the skills of cognitive computing, artificial intelligence and machine learning in the field of data engineering to develop intelligent systems.

PSO2: Data Driven Systems: Use modern tools and techniques to solve problems in Machine Learning, Deep Learning, Computer Vision and Natural Language Processing.