About the Department
Along with courses that provide specialization in AI, students will also have options to explore some applied domains such as computer vision, natural language processing, robotics, data analytics, and computer security. This enables the B. Tech. in AI graduates to take up careers in R&D positions in Industry, academia, and research laboratories. The 4-year undergraduate program is divided into 8 semesters, with each year containing 2 semesters.
The course content provides the students with proper insight about the domain of Artificial Intelligence with a firm foundation in ‘Mathematics for Artificial Intelligence. The carefully designed syllabus provides the students with deep knowledge in the core areas of Algorithm analysis and design, Modern Computer Architecture, foundations of Artificial Intelligence, Data Science and Machine Learning and Parallel and Distributed Data Management, etc.
AI and Data Science is the current trend ruling the business world and it is a highly paid career now. Artificial Intelligence and data science is a suitable course for those who would like to develop various intelligent business solutions. Big data solutions have changed the way business models are built and run. This study contributes much in manufacturing, e-commerce, banking, finance, transport, and healthcare industry.
The Core courses give them sufficient expertise in the areas of Algorithm Analysis and Design, Modern Computer Architecture, Artificial Intelligence Foundations, Data Science and Machine Learning, Parallel and Distributed Data Management, etc. Elective courses include various application domains of AI such as Robotics, Video/Image Analytics, Medical Signal Processing, Agents Based Systems, Data Mining and Business Analytics, Natural Language Processing, Wireless Sensor Networks, Internet of things, etc.
Once they complete the course, students get opportunities to get fully paid Internships and placement offers at MNCs and IT/ITES companies like Intel, Cerner, Robert Bosch, DELL, etc. Also, they could publish quality research papers of the case studies/dissertations done as part of their B. Tech. program.
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.
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.
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.
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.
- 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.
|1||Dr. Bhuvaneshwari. K. S.||Professor & Head||M.E., Ph.D||02-06-2014|
|2||Mr. Manikandan S||Assistant Professor||M.Tech||16-12-2013|
|3||Mr. Surenther I||Assistant Professor||M.E||03-04-2019|
|4||Ms. Sathya K||Assistant Professor||M.E||02-08-2021|
|5||Ms. Nivetha S||Assistant Professor||M.E||01-04-2022|
|6||Ms. Dhivya P||Assistant Professor||M.E||06-06-2022|
|7||Mr. Karthikeyan G||Assistant Professor||M.E||13-06-2022|
|8||Mr. Sakthivadivel||Assistant Professor||M.E||20-07-2022|
|9||Mr. Rajkumar R||Assistant Professor||M.E||25-08-2022|
|Core||Addition to Core|
Foundation of AI
RPA / Robotics
- 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
|IN GLOBAL||IN INDIA|
|Tata Consultancy Services
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