To make students engineering professionals, innovators or entrepreneurs engaged in technology development, technology deployment, or engineering system implementation in industry. To make students successful in applying modern computer science practice in data science, cyber security management as per Business needs in the international market.
To make students continue to acquire and demonstrate the professional skills necessary to be competent employees, assume leadership roles, and enjoy career success and satisfaction. To make students a productive citizen demonstrating high ethical and professional standards, make sound engineering or managerial decisions, and have enthusiasm for the profession and professional growth

A graduate of the Computer Science and Engineering Program will demonstrate: 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. Having an ability to be socially intelligent with good SIQ (Social Intelligence Quotient) and EQ (Emotional Quotient)
Having Sense-Making Skills of creating unique insights in what is being seen or observed (Higher level thinking skills which cannot be codified) The Graduates are expected to Create, choose, and apply suitable methodologies, resources, and modern engineering such as IT tools, including prediction and modeling to complex engineering activities, while keeping in mind the required limitations. The Graduates are expected to communicate efficiently with the engineering community and society at large on complex engineering tasks, such as being able to comprehend and write appropriate reports and design documents, give and receive specific guidance.

 Ability to develop a basic understanding of AI building blocks presented in intelligent agents. Ability to choose an appropriate problem-solving method and knowledge representation technique. Ability to analyse the strength and weaknesses of AI approaches to knowledge– intensive problem solving. Ability to design models for reasoning with uncertainty as well as the use of unreliable information.