The Department of Artificial Intelligence & Machine Learning was established in 2021.with the vision of creating industry-ready professionals equipped with cutting-edge skills in AI, ML, and data-driven technologies. Since its inception, the department has been committed to providing high-quality education that empowers students to build impactful careers in industries, research organizations, and academia.

The B.Tech program in Artificial Intelligence & Machine Learning is designed to impart strong theoretical foundations along with hands-on exposure to emerging domains such as deep learning, data science, computer vision, natural language processing, and intelligent systems. Through project-based learning and industry-aligned coursework, students gain the ability to analyze, design, and develop intelligent solutions to real-world societal and technological problems.

The department has shown remarkable progress in a short span, fostering a culture of innovation, research, and continuous learning. Students undertake real-world projects that help them understand the end-to-end process of problem solving and prepare them for industry expectations. Graduates of the AIML program pursue higher studies (MS and Ph.D.) at reputed international universities also Student Exchange Programme like @Aivancity School of AI & Data for Business & Society,  (Foreign) Hsieh, Cheng-Chun ( Oscar )National University of Kaohsiung, Taiwan Exchange period :15th July 2025 to 6th June 2026

The Department of AIML continues to strive toward academic excellence, nurturing skilled professionals who will contribute to the advancement of intelligent technologies and play a pivotal role in the digital transformation of society.

Curriculum Highlights :

Our Department offers choice based credit system (CBCS), which provides an opportunity for the students to choose courses from the prescribed courses comprising core, elective/minor or skill based courses. The AI/ML Engineering curriculum has been developed by considering the industry needs and technologies. Open electives are introduced from first year to final year to allow students to choose various horizons in AI/ML domain. In first year there are open electives and language courses, in second year students have open elective based on professional skill development courses, in third and final year program electives based on the various verticals such as data analysis, deep learning, natural language processing and so on are floated and in the eighth semester students are given a choice of three tracks viz. Industry Internship and Project, Undergraduate Research Experience and Entrepreneurship Development

The curriculum prepares students to tackle industrial and societal problems by applying gained domain knowledge. Students will learn best practices in solving real world problems by applying sequential methods of problem identification, formulation, design, develop, deploy and maintenance.

Students learn to use the latest programming languages along with necessary domain knowledge as and when required. Students will be given the opportunity to hone their skills in effectively by selecting one of the three tracks as per their choice. Three tracks are: Industry Internship & Project (IIP), Undergraduate Research Experience (URE), Entrepreneurship Development (ED).

Teaching and Learning Process at the Department :

To improve the learning ability of the students, department has implemented outcome based education. In the outcome based education, the focus shifted from teaching to learning of the students. Student cantered learning promotes active participation of students in teaching and learning process. In order to achieve the outcomes, faculty designs student centered teaching-learning and assessment methods. Some of the student centred teaching –learning methods adapted by the faculties of the department are Problem based learning, Project Based Learning,

This makes learning a joyful experience for students MOOCs, Blended MOOCs from IITs ,online courses like NPTEL, Coursera, Swayam etc. are also added in the teaching learning process. In focus of Industry need, various industry expert sessions / training programs are organized for the students, to bridge the gap between industry and academics. Along with final year major project, mini projects have been introduced at First, second and third year level. Not only academics but the student’s overall personality development is being taken care of by introduction of courses like Professional skill development.

Acquired Skills

The Artificial Intelligence & Machine Learning curriculum focuses on the following key skills:

• Machine Learning
• Deep Learning
• Data Analysis & Visualization
• Natural Language Processing
• Computer Vision
• Big Data & Cloud Computing
• AI Model Deployment
• Programming & Software Development

Examination and Evaluation :

ISE

In Semester Evaluation will be conducted for 20% by practicing different methods like

• • Moodle discussion Forum: This discussion Forum is for students who wish to learn efficiently respective course through discussing in Group. You will find an answer to questions and it can promote collaboration, and offer individuals room to explore topics, issues, and/or questions. A discussion forum is an excellent tool for students who may feel more comfortable expressing their understanding of course content in a written format, as opposed to verbally.
  • Evaluation through Active Learning Methods: We Use Activity based ISE evaluation like Project Based Learning.
  • CAS (Continuous Evaluation Sheet): we practice CAS Evaluation for group of experiments.
  • In Practical course evaluation will ask students to prepare an important questions on respective experiments and this will help students for GATE & interview preparation.
• Unit Test-I and II

Both tests will be conducted for 25 marks and which will be converted to 15 marks. 30% weightage given for these tests.

Unit Tests will be conducted on as per syllabus sequence like UT1 will be conducted on Chapter 1 & 2 and UT2 will be conducted on UT3 &4.

• ESE (End Semester Examination)

ESE will be conducted for 100 marks by considering whole syllabus of respective course and converted it into 50 marks. 50% weightage is given for ESE.

Centre of Excellence

• Juniper Networks

Facilities: Next Generation Firewall, Access switch, Core Switches, Access Points.

Benefits:

• AI Driven Campus Network Setup
• AICTE- EduSkills FDP for Faculty
• AICTE-Eduskills Virtual Internship
• Students Projects
• Industry Visits
• Joint Research Opportunity
• Global Certification Voucher Discount (70%)
• DOMO:

 Domo India Centre of Excellence empowers students with AI, ML, analytics skills, industry tools, and research opportunities..

Benefits:

• Gain job-ready skills in BI, AI, ML, and Data Analytics.
• Access to latest industry practices and tools.
• Increased employability through certifications.
• Participation in hackathons, projects, and innovation challenges.