Department of Artificial Intelligence and Data Science

About the Department

The B. Tech. in Artificial Intelligence and Data Science program at Karpagam College of Engineering is designed to prepare students for the future of technical education in AI and Machine Learning (ML). The curriculum offers a comprehensive understanding of AI and ML technologies, with courses covering specialized areas such as computer vision, natural language processing, robotics, data analytics, and computer security. Students gain deep knowledge in algorithm analysis, modern computer architecture, foundations of AI, data science, and machine learning, among other core areas.
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The program, spanning 4 years and divided into 8 semesters, equips students with the skills and expertise needed for R&D positions in industry, academia, and research laboratories. It also emphasizes practical applications through elective courses in domains like robotics, medical signal processing, data mining, business analytics, and more.

Upon completion, graduates have opportunities for fully paid internships and placements at top companies like Intel, Cerner, Robert Bosch, DELL, etc. The program’s focus on AI and data science prepares students for high-paying careers in industries such as manufacturing, e-commerce, banking, finance, transport, and healthcare, where intelligent business solutions and big data solutions are in high demand.

NVIDIA Ambassador

The Department of Artificial Intelligence and Data Science’s ambassadorship with NVIDIA’s academic programs highlights its dedication to cutting-edge technology education. This partnership offers students and faculty access to advanced resources, industry projects, and networking opportunities, shaping them into future tech leaders.

  • Organized student participation in three Nvidia GTC Global Conferences through NVIDIA academic programs.
  • Secured NVIDIA sponsorship for AI Lab equipment, including the NVIDIA DGX Server and Jetson Kit.
  • Industrial collaboration session at the NVIDIA Bangalore campus to foster industry partnerships and knowledge exchange.

Name of the startup: Insiflo AI Private Limited
Name of the students: Dhanavishnu A, Paushigaa S
Funds received for a startup: Microsoft startup fund

Name of the startup: Inogar Private Limited
Name of the students: Somanath T.G, Shaafiqe M, Dhyaneshwaran
Funds received for a startup: Raw materials support from Royal Universys

MoU and Academic Partners

Qlik, Tableau, NVIDIA, Databricks, Datacamp, JetBrains, and YardStick Digital Solutions, Krypc Technologies Pvt Ltd.


IIT Bombay Entrepreneurship cell, Royal Universys Webnet Private Limited, Analytics India Magazine.

Professional Bodies Membership


To become an integrative department through creativity and innovation in developing systems with Artificial Intelligence and Data Science to serve society.


  • Engage collaborative activities with the industry to produce industry-ready and future-ready talent.
  • Foster the spirit of lifelong learning in students through practical and social exposure beyond the classroom.
  • Provide multi-disciplinary research and innovation driven academic environments.
  • Practice and instil the highest standards of professional ethics, transparency and accountability at all levels.


Programme Educational Objectives

  • PEO1: Graduates will be able to demonstrate technical skills, competency in Artificial Intelligence and Data Science, exhibit proficiency and team management capability with proper communication in the job environment.
  • PEO2: Graduates will be able to work effectively in multidisciplinary engineering projects and support the growth of the economy of a nation by becoming entrepreneurs with a lifelong learning practice.
  • PEO3: Graduates will be able to carry out the research in the contemporary areas of Artificial Intelligence, Data Science and address the basic needs of the society.
Programme Outcomes (POs)

PO1: Engineering knowledge

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 first 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 that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

PO4: 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.

PO5: 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.

PO6: 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.

PO7: 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.

PO8: Ethics

Apply ethical principles and commit to professional ethics and responsibilities and norms of the 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 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.

PO11: 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.

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.

Programme Specific Outcomes
  • PSO1: Demonstrate the knowledge of Artificial Intelligence, Machine Learning and Data Science for designing and developing intelligent systems
  • PSO2: Implement Artificial Intelligence and data science methods for solving a problem in multi-disciplinary areas and design novel algorithms.

S.No Name Designation Qualification DOJ
1 Dr. Bhuvaneshwari. K. S. Professor & Head M.E., Ph.D 02-06-2014
2 Dr. Karthik G Professor M.E, Ph.D 01-11-2021
3 Dr. Rajeswari P Professor M.E, Ph.D 08-05-2023
4 Dr. Madhumitha R Associate Professor M.Tech., Ph.D 11-06-2018
5 Dr. Guhan T Associate Professor M.E, Ph.D 05-12-2022
6 Dr. Malini G Associate Professor M.Tech, Ph.D 08-05-2023
7 Dr. Manikandan S Assistant Professor M.Tech, Ph.D 16-12-2013
8 Dr. Jothi Prakash V Assistant Professor M.E,Ph.D 05-05-2014
9 Mr. Surenther I Assistant Professor M.E 03-04-2019
10 Mr. Vikkram R Assistant Professor M.E 17-06-2019
11 Ms. Sathya K Assistant Professor M.E 02-08-2021
12 Mr. Varatharajan N Assistant Professor M.E, Ph.D 11-08-2021
13 Mr. Castro. S Assistant Professor M.E 18-08-2021
14 Mr. Navaneetha Krishnan M Assistant Professor MCA, M.E 06-09-2021
15 Mr. Nagaraj S Assistant Professor M.E 04-05-2022
16 Ms. Dhivya P Assistant Professor M.E 06-06-2022
17 Dr. Karthikeyan G Assistant Professor M.E, Ph.D 13-06-2022
18 Ms. Gayathri U Assistant Professor M.E 28-08-2023
19 Ms. Vishnupriya K Assistant Professor M.E 20-09-2023
20 Ms. Saranya N Assistant Professor M.E 01-04-2024
Domain to Deliver
Core Addition to Core
Data Science
Data Analytics
R Program
Foundation of AI
Machine Learning
Deep Learning
RPA / Robotics
Data Visualization
Computer Vision
Auto ML
Apache Spark
Apache Kafka
Apache Hadoop
Data Visualization
Lab Facilities
Job opportunities
  • AI Tech Lab
  • Microsoft lab
  • Data Centre
  • Computer Vision & IOT
  • Artificial Intelligence Engineer
  • Data Scientist
  • Business Intelligence Developer
  • Data Analyst
  • Product Analyst
  • Full stack developer
  • Machine Learning Engineer
  • Machine Learning Architect
Top companies Using AI and Data Science
Tata Consultancy Services
Tiger Analytics
Amazon India

B.Tech. – Artificial Intelligence and Data Science

  • Duration: 4 years (Regular) / 3 years (Lateral Entry)
  • No. of Semesters: 8 (Regular) / 6 (Lateral Entry)
  • No. of Seats: Total – 120
  • Eligibility: 10+2 system of Education. Must have secured a pass in Physics, Chemistry and Mathematics in the qualifying examination.
  • Scope for Higher Studies: M.E. / M. Tech. / MBA / M.S. / Researcher