4 years, 8 semesters
60 Seats
Please refer to the details in the handout document.
To be a center of excellence in artificial intelligence and machine learning education by nurturing globally competent professionals with strong technical expertise, ethical values, innovative mindsets, and leadership qualities, capable of contributing to industry, research, and societal development.
PEO 1: Graduates will apply strong foundations in artificial intelligence, machine learning, and allied computing domains to analyze, design, and implement solutions for real-world problems.
PEO 2: Graduates will build successful careers in industry, entrepreneurship, higher education, or research by effectively using emerging AI and ML tools, technologies, and best practices.
PEO 3: Graduates will demonstrate professional ethics, social responsibility, and awareness of the societal, legal, and ethical implications of artificial intelligence and machine learning applications.
PEO 4: Graduates will exhibit effective communication, teamwork, leadership, and a commitment to lifelong learning while working in multidisciplinary and globally diverse environments.
Engineering Graduates will be able to:
Engineering knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.
Problem Analysis: Identify, formulate, review research literature and analyse complex engineering problems reaching substantiated conclusions with consideration for Sustainable Development (WK1 to WK4).
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 (WK5).
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 (WK8).
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. (WK2 and WK6).
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 (WK1, WK5, and WK7).
Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws (WK9).
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, 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 (WK8).
Curriculum for the program includes adequate balance of fundamental / foundation, core and elective courses. The courses are based on a credit structure with 22-26 credit per semester totaling to around 152 credits over for the entire 4 years B Tech Program including 7 months of industry internship. Every course is assigned lectures and practical as per requirement. The program course content is reviewed every year with industry inputs and participation.
The school encourages students to learn through experiential mode along with class room delivery. The delivery is very actively supported by Learning Management System (LMS). The LMS facilitates learning beyond classroom through YouTube and other online courses and contents available on the net. Through this innovative teaching and learning process, students have ample opportunity to learn through different modes. The curriculum also emphasizes on continuous self-learning.
Evaluation is based on continuous assessment throughout semester with appropriate weightage for in semester work, as well as end semester exams. Different modes of evaluation like open book exam, quiz and viva are available for the faculty to ensure attainment of course and program out-comes as defined above.
To address the demand of current market, the start of art learning is given that expects 24×7 online learning content as a supplement to the classroom learning, several modes of delivery are available, in addition to project based learning, implementation of technology, projects executed in the industry, participation in international competitions, group work etc. This innovation in Pedagogy ensures that students have several learning opportunities matching to their aspirations.
Students completing the program are found to be highly employable due to the innovative teaching – learning process adopted along with different modes of evaluation and industry internship for experience. Due to the emphasis on continuous self-learning, students are ready to undertake research and problem-solving capabilities in different emerging and disrupting technologies. Several opportunities are available to the students to pursue entrepreneurial traits leading to initiation of start-ups.
