About The Department
The Artificial Intelligence and Data Science department were founded in 2020 with one undergraduate program affiliated with Anna University, approved by AICTE. This course aims to provide the core technologies such as artificial intelligence, data mining, and data modelling and give intensive inputs in machine learning and big data analytics. By the end of this course, the students will gain cross-disciplinary skills across fields such as statistics, computer science, machine learning, and logic, data scientists and will have career opportunities in healthcare, business, eCommerce, social networking companies, climatology, biotechnology, genetics, and other essential areas. The central focus of this programme is to equip students with statistical, mathematical reasoning, machine learning, knowledge discovery, and visualization skills.
Vision
To empower future engineers with artificial intelligence and data science excellence by imparting comprehensive education and training, fostering innovation and driving transformative change across industries and society as a whole.
Mission
To empower with the knowledge, skills, and perspective required to excel in artificial intelligence and data science.
To create an environment that nurtures creativity, critical thinking, and problem solving skills driving advancements.
To provide students with exposure to real-world challenges and opportunities, enabling them to develop industry-relevant skills and networks.
To empower students to become leaders and change-makers who drive digital transformation and address societal challenges through AI-driven solutions.
To cultivate a generation of AI professionals who contribute to the development and deployment of AI technologies with integrity and societal well-being in mind.
Programme Educational Objectives (PEOs)
PEO 1 : Utilize their proficiencies in the fundamental knowledge of basic sciences, mathematics, Artificial Intelligence, data science and statistics to build systems that require management and analysis of large volumes of data.
PEO 2 : Advance their technical skills to pursue pioneering research in the field of AI and Data Science and create disruptive and sustainable solutions for the welfare of ecosystems.
PEO 3 : Think logically, pursue lifelong learning and collaborate with an ethical attitude in a multidisciplinary team.
PEO 4 : Design and model AI based solutions to critical problem domains in the real world.
PEO 5 : Exhibit innovative thoughts and creative ideas for effective contribution towards economy building.
Programme Outcomes (POs)
Engineering Graduates will be able to:
Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
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.
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.
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.
Programme Specific Objectives (PSOs)
Graduates should be able to:
Evolve AI based efficient domain specific processes for effective decision making in several domains such as business and governance domains.
Arrive at actionable Foresight, Insight, hindsight from data for solving business and engineering problems
Create, select and apply the theoretical knowledge of AI and Data Analytics along with practical industrial tools and techniques to manage and solve wicked societal problems
Develop data analytics and data visualization skills, skills pertaining to knowledge acquisition, knowledge representation and knowledge engineering, and hence be capable of coordinating complex projects.
Able to carry out fundamental research to cater the critical needs of the society through cutting edge technologies of AI.
