DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE ENGINEERING
The Department of Artificial Intelligence and Data Science Engineering was started in the year 2022. The Department offers a 4-Year full time B. Engg programme in Artificial Intelligence and Data Science Engineering and it has a team of well-qualified faculty members with rich industrial and academic experience. The broad professional experience of the faculty members bring a flavor and strength to research and development activities of the department. ICT enhanced teaching techniques are also used in the department to supplement the regular chalk and talk lectures.The B. Engg curriculum envisages five elective courses in addition to the courses on basic science, humanities, basic engineering and core Artificial Intelligence and Data Science Engineering.
The basic objectives of this course is to train students with the next age of intelligence and analytics generated by machines, influencing the human lives to help improve efficiencies and augment human capabilities,influencing consumer products with significant breakthroughs in healthcare,manufacturing,finance and retail industry,will embark on a journey that explores the fascinating realm of cutting-edge AI technologies that are reshaping industries, revolutionizing decision-making, and transforming the way we interact with data/information.
The prescribed core courses cover important and exciting areas of Artificial Intelligence and Data Science Engineering including Artificial Intelligence and Data Science. As a part of the curriculum, the students are also given the best possible training in the Advanced Data Science and Artificial Intelligence Tools that are widely used in Companies.
AI&DS is an interdisciplinary branch of science,engineering and technology creating to complete ecosystem and widely used in almost every sector of the technical industry,academics and research.Key concepts and technologies include Machine Learning, Deep Learning, Fundamentals of AI, Natural Language Processing (NLP), Optimization, Bigdata Engineering, Data Visualisation, Responsible AI, Reinforcement Learning and Time Series Analysis.
Program Outcomes (POs):
PO 1:Engineering knowledge:Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution to complex engineering problems.
PO 2: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.
PO 3: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.
PO 4: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.
PO 5: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.
PO 6: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.
PO 7: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.
PO 8:Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO 9:Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO 10: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.
PO 11: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.
PO 12: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.
PROGRAM EDUCATIONAL OBJECTIVES (PEO s) of the Department:
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 life -long 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.
Program Specific Outcomes (PSOs) of the Department:
PSO 1:Evolve AI based efficient domain specific processes for effective decision making in several domains such as business and governance domains.
PSO 2:Arrive at actionable Foresight, Insight, hindsight from data for solving business and engineering problems.
PSO 3: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.
PSO 4: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.
PSO 5:Able to carry out fundamental research to cater the critical needs of the society through cutting edge technologies of AI.
AI&DS DEPARTMENT IS EQUIPPED WITH FOLLOWING LABORATORIES:
Data Science Lab
VISION OF DEPARTMENT
To Spring up as a “Centre of excellence in the field of Artificial Intelligence and Data Science” and to transfer the students by importing cognitive learning environment with Academia, Research, and Industry collaboration to address global challenges through novelty and sustainability.
MISSION OF DEPARTMENT
M1:To create next generation professionals who are skilled to perform intelligent data analysis and mimic human intelligence.
M2:: To develop practically trained professionals through the best possible teaching –learning methodology.
M3:To groom professionals with highly intelligent and ability to solve real-time problems.