Artificial Intelligence and Machine Learning

Department Details

The Department of Artificial Intelligence & Machine Learning was established to equip students with skills in cutting-edge technologies that drive automation, data-driven decision-making and innovation across industries. It prepares future engineers to solve complex real-world problems using intelligent systems and algorithms. The department is committed to deliver high-quality, industry – relevant education through a blend of strong theoretical foundations and practical learning. The teaching-learning process emphasizes outcome based education, incorporating modern pedagogies such as project-based learning, flipped classrooms and continuous assessment through assignments, coding exercises and real-world case studies. Students gain hands-on experience using advanced tools and technologies including python, Tensorflow and PyTorch. The department is supported by state-to-the-art infrastructure including AI and Deep Learning Labs, Data Science Labs, high performance computing facilities, smart classrooms and access to digital libraries & cloud platforms, ensuring an environment conducive to innovation, experimentation and interdisciplinary research.
Through internships, guest lectures, MoUs and industry-sponsored projects, the department actively fosters industry collaboration enabling students to stay aligned with current technological trends and workplace expectations. A dedicated placement and training cell prepares students with technical, aptitude and soft skills, resulting in strong placement outcomes in leading IT companies and startups. Graduates are well-equipped for diverse career opportunities such as machine learning, data scientist, AI engineer and roles in emerging domains like healthcare AI, robotics and smart systems. In addition, the department promotes research and innovation through publications, patents and participation in competitions & conferences, empowering students to pursue higher education, research careers or entrepreneurial ventures in the rapidly evolving AI landscape.

Vision

To transform students into technically skilled AI professionals, pioneering leaders and environmentally responsible citizens capable of addressing global and societal challenges through intellectual systems.

Mission

M1: Academic Excellence & Holistic Learning
To implement a holistic outcome-based AI & ML curriculum through advanced teaching, project-based learning and industry collaboration associated with global standards.
M2: Employability & Skill Development
To advance learners with strong technical proficiency, practical skills & Professional attitude to improve employability in AI-driven industries.
M3: Entrepreneurship & Leadership.
To nature innovation, leadership qualities and entrepreneurial approach, empowering students to become job originators & contribute to economic growth.
M4: Research & Innovation.
To promote research culture, interdisciplinary collaboration & problem-solving ability in emerging AI domains with societal & environmental relevance.
M5: Ethics & Responsibility
To inculcate professional ethics, environmental consciousness & social responsibility in developing AI solutions for sustainable development.

Program Educational Objectives (PEOs)

PEO1: Technical Expertise & Employability
Graduates will build successful careers in AI and ML by applying strong technical knowledge, practical skills, and professional competencies to solve real-world problems.
PEO2: Innovation, Research & Entrepreneurship
Graduates will demonstrate innovation, research aptitude, and entrepreneurial mindset to develop intelligent solutions and contribute to technological and economic growth.
PEO3: Ethics, Sustainability & Lifelong Learning
Graduates will engage in continuous learning and practice ethical, socially responsible, and environmentally sustainable approaches in developing AI-based systems.

Program Specific Outcomes (PSOs)

PSO1: AI System Development
Ability to design, develop, and deploy AI and ML models using modern tools and techniques to address real-world challenges.
PSO2: Data Analysis & Technical Proficiency
Ability to analyse complex data, apply appropriate algorithms, and utilize programming and AI frameworks for effective problem-solving.
PSO3: Innovation & Problem Solving
Ability to identify societal and industrial problems and develop innovative, interdisciplinary AI-driven solutions.
PSO4: Ethics & Professional Responsibility
Ability to apply ethical principles, environmental awareness, and social responsibility in the development and deployment of AI technologies.

Program Outcomes (POs)

1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
2. Problem analysis: Identify, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
3. 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.
4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
6. 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.
7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
10. 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.
11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
12. Life-long 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.