VISION

To emerge as a center of excellence in Artificial Intelligence and Data Science, empowering women graduates with strong analytical skills, ethical values, innovative thinking, and lifelong learning abilities to develop data-driven and intelligent solutions for industry, research, and societal advancement.

MISSION

• To provide strong foundations and practical skills in Artificial Intelligence, Data Science, and core computer science through effective teaching and modern learning resources.
• To encourage innovation, problem solving, and continuous learning by engaging students in projects, research activities, and emerging data-driven technologies.
• To prepare women students for successful careers and higher studies by nurturing professional competence, ethical values, and social responsibility.

• PO1 — Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
• PO2 — Problem Analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using principles of mathematics, natural sciences, and engineering sciences.
• PO3 — Design/Development of Solutions: Design solutions for complex engineering problems and design system components or processes to meet specified needs considering public health, safety, cultural, societal, and environmental aspects.
• PO4 — Conduct Investigations of Complex Problems: Use research-based knowledge and research methods including design of experiments, analysis, and interpretation of data to provide valid conclusions.
• PO5 — Modern Tool Usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools to complex engineering activities, with an understanding of their limitations.
• PO6 — The Engineer and Society: Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal, and cultural issues relevant to professional engineering practice.
• PO7 — Environment and Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate knowledge of and need for sustainable development.
• PO8 — Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice.
• PO9 — Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams and in multidisciplinary settings.
• PO10 — Communication: Communicate effectively on complex engineering activities with the engineering community and society at large, including writing reports, design documentation, making presentations, and giving/receiving clear instructions.
• PO11 — Project Management and Finance: Demonstrate knowledge and understanding of engineering and management principles and apply these to one’s work as a member and leader in a team to manage projects and in multidisciplinary environments.
• PO12 — 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.

• PEO1: Graduates will apply principles of Artificial Intelligence, Data Science, and computer science to analyze, design, and develop data-driven solutions for real-world problems.
• PEO2: Graduates will pursue successful careers in industry, higher education, research, or entrepreneurship by continuously enhancing their technical, analytical, and professional skills.
• PEO3: Graduates will demonstrate ethical conduct, teamwork, leadership qualities, and social responsibility while contributing to technological innovation and societal development.

• PSO1: Ability to design, implement, and evaluate data-driven and intelligent systems using data analytics, machine learning techniques, programming tools, and modern computing platforms.
• PSO2: Ability to apply Artificial Intelligence and Data Science techniques such as statistical analysis, data visualization, predictive modeling, deep learning, and big data technologies to solve industry-oriented and societal problems.

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