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TNEA CODE 2656 2656

Artificial Intelligence & Data Science

Genesis

The Department of Artificial Intelligence & Data Science, started in the year 2021, offers B.Tech  Artificial Intelligence & Data Science to meet the challenges of higher education, research and innovation in key areas of Data Science and AI. The department aims to develop AI and Data Science engineers who are innovative and entrepreneurial to become global leaders in research and technology. 

Vision

To develop and nurture technically sound Artificial Intelligence and Data Science Professionals to meet industrial expectations through academics and research.

Mission

M1: Nurture and enrich the students to have a strong caliber and domain expertise for a successful academic career in Artificial Intelligence and Data Science.

M2: Foster a holistic learning environment that cultivates multidisciplinary skills with AI innovation, based on industrial requirements.

M3: Prepare students to make impactful contributions to society by pursuing research activities and upholding ethical principles.

Program Objectives
  • Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and Artificial Intelligence and Data Science basics to the solution of complex engineering problems.

  • Problem analysis: Identify, formulate, review research literature, 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 research-based 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 modeling 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 write 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.

Graduates should be able to

  • generate actionable foresight, insight, hindsight from Data, develop Data Analytics and Data Visualization Skills using industrial-standard tools and techniques to solve complex Business and Engineering problems.
  • conduct fundamental research to cater the critical needs of society through cutting-edge AI technologies.
Graduates can

PEO1: utilize their proficiencies in the fundamental knowledge of Basic Sciences, Mathematics, Artificial Intelligence, Data Science and Statistics, to build systems that require the management and analysis of large volumes of data.

PEO2: advance their technical skills to pursue pioneering research in the field of Artificial Intelligence and Data Science and provide sustainable solutions for the ecosystem’s welfare.

PEO3: think logically, pursue lifelong learning, and collaborate with an ethical attitude to design and model AI-based solutions for critical real-world problems, making a positive impact on society.

B.Tech (AI&DS)
0 seats
Intake
  • 4 years Anna University Curriculum
  • Industry Internship with Stipend 
Salient Features
Laboratories

The Artificial Intelligence & Data Science has 312 computers with high end configuration distributed across seven laboratories with four Blade-Mounted Servers. 

Faculty Team
S.NO. NAME DESIGNATION DOJ QUALIFICATION NATURE OF ASSOCIATION
1 Dr.S.SELVI Associate Professor & Head 08-07-2022 M.E., Ph.D. Regular
2 Dr.P.VISHNU RAJA Professor 22-01-2024 M.E., Ph.D. Regular
3 Mr.C.PALANI NEHRU Assistant Professor 07-12-2022 B.E., M.E., Regular
4 Mr.V.RAJARAM Assistant Professor 28-07-2023 MCA., M.E., Regular
5 Ms.P.BRINDHA Assistant Professor 08-08-2022 B.E., M.E., Regular
6 Ms.M.NIVETHINI Assistant Professor 19-07-2023 B.E., M.E., Regular
9 Ms.R.KIRTHIGA Assistant Professor 22-01-2024 B.E., M.E., Regular
Dr. S. SELVI
Head of the Department

Teaching: 16.9 Years

Dr. P. VISHNU RAJA
Professor
Mr. V. RAJARAM
Assistant Professor
Mr. C. PALANI NEHRU
Assistant Professor
Ms .P. BRINDHA
Assistant Professor

Teaching: 18.6 Years

Teaching: 12 Years

                Teaching: 9.8 Years

Teaching: 8 Years

Ms. M. NIVETHINI
Assistant Professor
Teaching : 4 Years
Ms. R. KIRTHIGA
Assistant Professor
Admission 2024-25 Open
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