About Us

B.Tech in Artificial Intelligence and Data Science (AID) is one of the most prominent and future-focused engineering disciplines today. This program blends core computer science principles with advanced AI techniques and data analytics, enabling students to solve real-world problems using machine learning, big data, deep learning, and predictive modeling.

The Department of Artificial Intelligence and Data Science was established in the year 2021 with an intake of 60 students in the B.Tech program. The department is equipped with well-furnished laboratories, modern computing infrastructure, and a high-speed internet network to support hands-on experiments and research.

The Department maintains high academic standards to provide quality education and practical exposure. Our experienced, qualified, and research-driven faculty, along with a skilled technical support team, guide students toward acquiring the expertise and professionalism needed to meet the growing demand for AI and data science specialists in industry, research, and entrepreneurship.

Program Outcomes (POs)

PO1: Engineering knowledge:
Apply knowledge of mathematics, statistics, computer science, and engineering fundamentals to solve complex engineering problems in artificial intelligence and data science.

PO2: Problem analysis:
Identify, formulate, and analyze complex AI and data-centric problems using research literature and data-driven techniques to draw meaningful conclusions.

PO3: Design/development of solutions:
Design effective AI- and data-based solutions that meet specified requirements with due attention to public safety, societal well-being, ethics, and sustainability.

PO4: Conduct investigations of complex problems:
Employ research methods, tools, and experiments in AI and data science to interpret data, extract knowledge, and synthesize valid conclusions.

PO5: Modern tool usage:
Create, select, and apply appropriate AI and data science tools, programming frameworks, and IT resources to solve complex engineering problems with an understanding of their limitations.

PO6: The engineer and society:
Assess the societal, legal, and cultural implications of AI and data science solutions to ensure responsible innovation and practice in diverse engineering contexts.

PO7: Environment and sustainability:
Understand the impact of AI and data-driven engineering solutions on the environment and advocate sustainable approaches for future generations.

PO8: Ethics:
Commit to professional ethics and responsibilities, applying honesty, integrity, and confidentiality in handling data and intelligent systems.

PO9: Individual and team work:
Function effectively as an individual and as a member or leader in diverse teams, demonstrating strong interpersonal skills in multidisciplinary and collaborative settings.

PO10: Communication:
Communicate technical concepts and project outcomes clearly and confidently through reports, presentations, and visualizations tailored to professional and public audiences.