SRM TRP Engineering College
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The Department of Artificial Intelligence and Data Science (AI&DS) is designed to meet the evolving demands of the digital era by training students in cutting-edge technologies like machine learning, deep learning, data analytics, natural language processing, and big data. With a future-focused curriculum, state-of-the-art labs, and experienced faculty, the department emphasizes both theoretical foundations and practical applications. Students are encouraged to participate in live...


To develop skilled Artificial Intelligence and Data Science cprofessionals for intelligent analytics and sustainable technological advancement.

Programme Outcomes, Programme Specific Outcomes, and Programme Educational Objectives
The graduates of Artificial Intelligence and Data Science will achieve the following milestones:
PEO1: Apply Artificial Intelligence and Data Science principles to analyze complex data and develop intelligent solutions.
PEO2: Utilize computational methods, analytics, and emerging technologies for innovation and societal advancement.
PEO3: Demonstrate ethical responsibility, leadership qualities, and collaborative skills in multidisciplinary environments.
PEO4: Pursue careers, research, entrepreneurship, and higher education in Artificial Intelligence and Data Science domains.
PEO5: Engage in lifelong learning and adaptability towards evolving intelligent technologies.
PO1: Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.
PO2: Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)
PO3: Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)
PO4: Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions. (WK8).
PO5: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)
PO6: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7).
PO7: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)
PO8: Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.
PO9: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences
PO10: 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.
PO11: Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change.
Students of Artificial Intelligence and Data Science will develop professional competency to:
PSO1: Design data-driven intelligent solutions using Artificial Intelligence, predictive analytics, data engineering, and advanced learning algorithms.
PSO2: Apply cloud analytics platforms, responsible AI methodologies, and intelligent decision systems for solving multidisciplinary industrial and societal challenges.
Download important course documents and resources
Access the official regulation documents that outline the academic framework, course structure, evaluation criteria, and compliance requirements for this program.
Download the complete curriculum and syllabus documents containing detailed information about course content, learning objectives, textbooks, references, and assessment methods.
SRM TRP Engineering College
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