Department
Department
The AIML (Artificial Intelligence and Machine Learning) Department is a dynamic and rapidly growing academic unit. The department is known for fostering strong technical, analytical, and practical skills, supported by well-qualified faculty members with excellent technical knowledge and rich industry expertise. It emphasizes quality education, innovation, collaborative learning, and experiential learning, providing a solid foundation in AI and ML concepts. With an industry-aligned curriculum, practical exposure, research-oriented learning, and effective mentorship, the department creates a supportive environment that prepares students to meet modern academic and industry challenges while developing both professional competence and personal growth.
To develop competent AI & ML professionals through innovative, creativity, experiential learning and emerging as a centre of excellence that address regional, national, and global challenges for industry and society.
To cultivate a dynamic and inclusive learning environment that inspires creativity, innovation, and practical expertise in AI & ML.
To establish the department as a centre of excellence in experiential learning, research-driven approach, and innovation in Artificial Intelligence.
To promote lifelong learning and ethical responsibility while addressing the evolving needs of industry and society.
To advance multidisciplinary research and education fostering global perspectives, employability, and ethical, value-driven thinking.
Engineering Knowledge:
Apply knowledge of mathematics, natural science, computing, engineering fundamentals, and an engineering specialization to develop solutions to the complex engineering problems.
Problem Analysis
Identify, formulate, review research literature, and analyze complex engineering problems, reaching substantiated conclusions with consideration for sustainable development.
Design/Development of Solutions
Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society, and environment as required.
Conduct Investigations of Complex Problems
Conduct investigations of complex engineering problems using research-based knowledge, including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions.
Engineering Tool Usage
Create, select, and apply appropriate techniques, resources, and modern engineering & IT tools, including prediction and modelling, recognizing their limitations to solve complex engineering problems
The Engineer and The World
Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture, and environment.
Ethics
Apply ethical principles and commit to professional ethics, human values, diversity, and inclusion; adhere to national & international laws.
Individual and Collaborative Team work
Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.
Communication
Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, and make effective presentations considering cultural, language, and learning differences.
Project Management and Finance
Apply knowledge and understanding of engineering management principles and economic decision-making, and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.
Life-Long Learning
Recognize the need for, and have the preparation and ability for i) independent and life-long learning, ii) adaptability to new and emerging technologies, and iii) critical thinking in the broadest context of technological change.
POS 1
Able to design, develop, and deploy intelligent systems using machine learning and data-driven approaches to solve real-world problems in various domains.
POS 2
Apply AI and ML tools and technologies to build efficient, ethical, interpretable, and secure solutions for emerging domains with responsible use of artificial intelligence.
PEO's 1
Graduates will utilize strong foundations in mathematics, computing, artificial intelligence, and machine learning to design and implement effective solutions for real-world challenges.
PEO's 2
Graduates will acquire robust technical knowledge, analytical skills, and practical experience in AI & ML to achieve successful career in industry, research, or innovation.
PEO's 3
Graduates will communicate effectively, work collaboratively in teams, demonstrate ethical leadership, and pursue lifelong learning for continuous professional growth.
Associate Professor & Head of Department
AI & ML
Welcome to the Department of Artificial Intelligence and Machine Learning. The Department of Artificial Intelligence and Machine Learning is dedicated to excellence in education, research, and innovation. Department aims to develop skilled, ethical, and industry-ready professionals through a strong academic foundation, experiential learning, and continuous engagement with emerging technologies. The department encourages creativity, critical thinking, and problem-solving skills to equip students to meet future challenges with confidence. Students are actively motivated to undertake internships with leading organizations and engage in real-life, industry-oriented projects. The faculty of the department strive hard to achieve these goals. The department regularly organizes seminars, expert sessions, conferences, certification programs, and training sessions to ensure students develop students globally and remain competitive in the evolving technological landscape. I warmly welcome you to join DYP-UT and become part of a vibrant academic community that strives for excellence, innovation, and meaningful contributions in the field of Artificial Intelligence and Machine Learning.
Select a program to view its course structure, board of studies, time table and previous question papers.