PEO, PO & PSO

Cognizance Competency

To transform students into graduates in the field of Computer Science and Engineering by strengthening their mathematical fundamentals, algorithmic principles, and program designing concepts in order to analyze and solve current challenges.

Proficiency and Governance

To develop graduates with logical and reasoning skills, enabling them to effectively work within multidisciplinary teams and exhibit leadership qualities for the betterment of society.

Comprehensive Engineer

To equip graduates with innovative ideas and technical skills, enabling them to adapt to emerging technologies in industry, as well as contribute to research and development initiatives.

Engineering graduates will be able to:

• Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and specialization to solve complex problems.
• Problem Analysis: Identify, formulate, and analyze complex engineering problems using mathematical and scientific principles.
• Design/Development of Solutions: Design solutions for complex engineering problems considering safety, societal, and environmental factors.
• Investigations of Complex Problems: Conduct experiments, analyze data, and provide valid conclusions using research-based knowledge.
• Modern Tool Usage: Apply appropriate tools, technologies, and software to solve complex engineering tasks efficiently.
• Engineer and Society: Assess societal, health, safety, and legal issues with professional responsibility.
• Environment and Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts.
• Ethics: Commit to professional ethics and responsibilities of engineering practice.
• Individual and Team Work: Function effectively as an individual and as a leader in multidisciplinary teams.
• Communication: Communicate effectively in verbal and written forms with technical and non-technical audiences.
• Project Management and Finance: Apply engineering and management principles to manage projects efficiently.
• Life-long Learning: Recognize the need for continuous learning and adaptability in technological changes.

• Core Oriented: Proficient in the field of metalogic, hardware, and software computing to solve complex problems.
• Continuous Improvement: Sustain and innovate in a dynamic environment by developing algorithms and projects using efficient data structures and open-source tools.
• Intra-disciplinary: Apply knowledge in various domains such as data management science and cognitive technologies.
• Focusing Growth: Excel in innovation using state-of-the-art methodologies focused on optimization and quality improvement.