Minor Course in Computational Mathematics for Engineers
(2023 Admission onwards)
The emergence of AI requires engineers to have new understanding in mathematics and computing. Computational mathematics, with a concentration on computational algebra, numerical computing, computational probability, and numerical optimization, forms the foundation of advanced computational approaches. Traditional engineering UG curricula do not cover the vast range of computational methods utilized in industry, even while they do teach significant analytical techniques pertinent to the particular discipline of engineering. As a result, graduates of standard engineering programs have little experience with these techniques. Currently, employers are searching for applicants with prior experience rather than investing significant time and funds in training these grads. However, there isn’t enough space in the current curriculum for such skill development. A new inter-disciplinary minor program in computational mathematics has been introduced to fill this important but difficult gap in engineering education. Its goal is to produce graduate engineers who are proficient in the use of contemporary computational methods for a wide range of advanced applications and research.
Programme Outcomes (POs) and Programme Specific Outcomes (PSOs)
|Engineering knowledge: Apply the knowledge of applied & computational mathematics, science, engineering fundamentals, and an engineering specialization to solve complex engineering problems.
|Identify, formulate, review scientific updates, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
|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.
|Conduct investigations of complex problems: Use mathematical knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
|Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.
|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
|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.
|Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
|Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
|Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and generate/ automate effective reports and design documentation, make effective presentations, and give and receive clear instructions.
|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.
|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.
|Acquire proficiency in implementing computational techniques.
|Successfully apply Computational Mathematics in Engineering Problem Solving.
|Competently analyze and convey scientific results while abiding by the relevant engineering requirements.
The total credit for the minor programme is 20. There are four 4-credit courses with equal importance to computational theory, practicals, and a minor project at the end. For each course, there are two theory sessions and two laboratory sessions per week.