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M.TECH. MACHINE DESIGN

The M.TECH. VLSI & EMBEDDED SYSTEMS department at AMC Engineering College teaches students the basics and advanced concepts of AI, Machine Learning, and Data Science. The course includes both classroom learning and practical experience through labs, projects, internships, and hands-on activities. Students learn from experienced teachers and have access to modern facilities. The department also organizes workshops, seminars, and hackathons to improve skills and knowledge. Industry partnerships, research opportunities, and placement training help students build their careers and become job-ready. The program aims to prepare students for successful careers in AI and Machine Learning.

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All Programmes > M.TECH. MACHINE DESIGN

Vision and Mission of the Programme
  • Vision: "To be a premier Department in the field of Artificial Intelligence and Machine Learning to meet the future needs of the society".
  • Mission: M1: To provide state of art infrastructure, academic excellence facilities and research with innovative ICT in AI & ML.
  • M2: To provide hands on experience in the advanced tools and technologiesin the field of expert systems and neural networks.
  • M3: To collaborate industry institute interaction and prepare students ready for the next generation technological needs of the society.
  • M4: To mould students into professionally competent, socially Responsible and ethically correct AI&ML professional.
Programme Specific Outcomes
  • PSO1: Ability of applying soft computing techniques, Deep learning, Data structures, Computational Intelligence Algorithms, Expert Systems and Neural Networks.
  • PSO2: Software skills and ability of developing advanced training modules using machine learning techniques and evolutionary algorithms.
Programme Outcomes
  • 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 asrequired. (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. (WK8)
Course Outcomes
  • Upon Successful Completion of AIML Department Courses Students are able to Develop models in Data Science, Machine learning, Deep learning, and Bigdata technologies, using acquired AI knowledge and modern tools and Formulate solutions for interdisciplinary problems through acquired programming knowledge in the respective domains complying with real-time constraints
Programme Educational Objectives
  • PEO1: Graduate acquires advanced knowledge and skills of AI&ML and develop leadership skills to drive the society.
  • PEO2: Graduates of programme will apply AI&ML tool in real time problems for enhancing knowledge in the inter disciplinary research and startups.
  • PEO3: Graduate adopt value-based proficiency in solving expert level problems.
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