Counselling Code: 2719
The Department of Artificial Intelligence and Data Science, established in 2020, is committed to nurturing future-ready professionals through a strong blend of academic excellence, advanced infrastructure, and deep industry integration. At its inception, the department was supported by Robert Bosch Pvt. Ltd. as a Knowledge Partner, laying a strong foundation aligned with industry needs.The department houses a Centre of Excellence in Artificial Intelligence and Robotics, sponsored by Craftsman Automation, which is equipped with state-of-the-art NVIDIA GPU infrastructure and Jetson Orin kits to support cutting-edge research and hands-on learning in AI, deep learning, and robotics.A key highlight of the department is its association with Cognizant Technology Solutions through the Digital Nurture Partner Network (NPN) program, which equips students with industry-relevant digital skills and enhances their employability. The department has also signed an MoU with GUVI HCL, through which selected core courses across semesters are designed and delivered in collaboration with industry experts. Programming courses are offered through the NeoColab platform, enabling experiential and practice-oriented learning.To further strengthen its academic–industry ecosystem, the department has established MoUs with Resilience Business Grids LLP (RBG.AI), ConnectIndia Pty Ltd, Melbourne (Australia), and Selsoft. These collaborations support curriculum development, internships, live projects, faculty development, and specialized domains such as Intelligent Systems.Faculty members actively engage in consultancy projects with reputed organizations such as L&T Technology Services Ltd. and UI Bridge Solutions Pvt. Ltd., while students gain valuable industry exposure through internships at leading companies including Bosch Global Software Technologies Pvt. Ltd., L&T Technology Services Ltd., Edsols Innovations Pvt. Ltd., Code Magen, and Soliton. Students have consistently excelled in corporate-level hackathons, earning prestigious awards and cash prizes, and also excel in co-curricular and extra-curricular activities. The department is further enriched by global expertise through Dr. Suresh Rajappa, Executive Director, KPMG LLP, USA, who serves as Adjunct Faculty. Overall, the department offers a vibrant ecosystem that fosters innovation, industry relevance, and academic excellence in Artificial Intelligence and Data Science.
The Department of Artificial Intelligence and Data Science, established in 2020, is committed to nurturing future-ready professionals through a strong blend of academic excellence, advanced infrastructure, and deep industry integration. At its inception, the department was supported by Robert Bosch Pvt. Ltd. as a Knowledge Partner, laying a strong foundation aligned with industry needs.The department houses a Centre of Excellence in Artificial Intelligence and Robotics, sponsored by Craftsman Automation, which…
Dr. V. Karpagam is a Professor and Head of the Department of Artificial Intelligence and Data Science at Sri Ramakrishna Engineering College, Coimbatore, with over 27 years of academic experience. She holds a Ph.D. in Information and Communication Engineering from Anna University, Chennai, along with a Master’s degree in Software Engineering and a Bachelor’s degree in Computer Science and Engineering. She is a recognized Anna University Research Supervisor and is…Readmore
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VISION
To achieve excellence
in the domain of Artificial Intelligence and Data Science and produce globally
competent professionals providing
multidisciplinary, sustainable solutions for societal challenges and industrial
needs.
MISSION
M1:To deliver quality education to develop ethical and sustainable intelligent solutions for
interdisciplinary domains.
M2:To promote research, innovation, and entrepreneurship through collaboration with
industry and academia.
M3:To foster leadership and lifelong learning for professional and societal advancement.
PEO 1: Demonstrate professional and research competence using combined
knowledge in Mathematics, Computing, Artificial Intelligence and Data Science
PEO 2: Apply knowledge and skills in Artificial Intelligence and Data Science to
develop innovative, sustainable and ethically responsible solutions to complex,
multidisciplinary problems
PEO 3: Engage in constructive research, professional growth and lifelong
learning by effectively applying emerging technological expertise
Program Outcomes as stated by NBA: Engineering Graduates will be able to
1.EngineeringKnowledge:
Apply knowledge of mathematics, science, engineering
fundamentals, and an engineering specialization to solve complex engineering
problems.
2.Problem
Analysis: Identify, formulate, review research literature, and
analyze complex engineering problems to reach substantiated conclusions for
sustainable development.
3.Design/Development
of Solutions: Design solutions for complex engineering problems and
design system components or processes that meet specific needs with appropriate
consideration for public health and safety, and cultural, societal, and
environmental considerations.
4.Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge, including the design of experiments, modeling, analysis, and interpretation of data to provide valid conclusions
5 .Modern
Tool Usage: Create, select, and apply appropriate techniques,
resources, and modern engineering and IT tools—including prediction and
modeling—while recognizing their limitations, to solve complex engineering
problems.
6.The
Engineer and the World : Analyze and evaluate societal and environmental
aspects while solving complex engineering problems to assess sustainability
impacts with reference to economy, health, safety, legal framework, culture,
and environment.
7. Ethics: Apply
ethical principles and commit to professional ethics, responsibilities, and
norms of engineering practice.
8.
Individual and Team Work: Function effectively as an individual and as a member
or leader in diverse and multidisciplinary teams.
9.
Communication: Communicate effectively and inclusively within the
engineering community and society at large, by being able to comprehend and
write effective reports and design documentation, and make effective
presentations considering cultural, language and learning differences.
10. Project
Management and Finance: Apply knowledge and understanding of engineering
management principles and economic decision-making and apply these to one’s own
work, as a member and leader in a team, and to manage projects and in
multidisciplinary environments.
11.
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.
PSO1: Analyze, design and develop sustainable intelligent solutions to address
complex challenges posed by industry and society.
PSO2: Demonstrate data analysis skills to achieve effective insights and decision
making to solve real-life problems.
PSO3: Apply mathematical and statistical techniques to model real-world
problems using appropriate AI algorithms.
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21-Mar-25
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20-Sep-24
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