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    Artificial Intelligence and Machine Learning (AIML) Department


    Department Menu About Department Vision & Mission Faculty Program Educational Objectives (PEOs) Program Specific Outcomes (PSOs) Program Outcomes (POs) Contact Us
    About Department

    The 4-year B.Tech program in Artificial Intelligence and Machine Learning (AIML) focuses on complex inputs and outputs that are used to make decisions or enhance human capabilities.

    The Artificial Intelligence degree offers courses that span across computer science, AI/machine learning, mathematics/statistics, computational modeling skills, domain knowledge and neural networks. The AIML degree will prepare students to stand out in one of the world's fastest-growing careers. Graduate of B.Tech in CSE (AIML) will acquire computer science skills with the added expertise in artificial intelligence and machine learning to work across many sectors, including medicine, finance, robotics, and business intelligence.

    Graduates of B.Tech in CSE (AIML) will be well-prepared to work across many sectors, including medicine, finance, robotics, and business intelligence. Artificial intelligence engineer, Software Developer, Robotic Programmer, Data analyst etc.

    In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding where AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.

    Machine Learning is a subset of artificial intelligence closely related to computational statistics which focuses on making predictions using computers. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop conventional algorithms to perform the needed tasks. It's time to learn the future technology!

    Vision & Mission

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    Vision:

    The Department  of Artificial Intelligence & Machine learning will strive to  educate students to acquire AI/ML skills towards innovative research and entrepreneurial thinking and create solutions that benefit society and industry. 

    Mission:

    • Provide training to generate knowledge using the latest concepts and techniques in artificial intelligence and machine learning.
    • Train student's in Interdisciplinary skill sets technical skill through innovation and lifelong learning.
    • Cultivate a research-oriented mindset in students
    • Develop ethical professionals who can solve social and industrial challenges.
    Program Outcomes (POs)

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    1

    Engineering knowledge:

    Apply the knowledge of mathematics, science, engineering fundamentals and an engineering specialization to the solution of complex engineering problems.

    2

    Problem analysis:

    Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural science and engineering sciences.

    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.

    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.

    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

    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.

    7

    Environment sustainability:

    Understand the impact of the professional engineering solutions in the societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

    8

    Ethics:

    Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

    9

    Individual and team work:

    Function effectively as an individual and as a member or leader in diverse teams, and in multidisciplinary settings.

    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

    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.

    12

    Lifelong learning

    recognize the need for, and have the preparation and ability to engage in independent and lifelong learning in the broader context of technological change

     

    Program Educational Objectives (PEOs)

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    The graduates of the programme are able to:

    PEO1: analyze and solve Engineering problems with through modern computing techniques.
    PEO2: Demonstrate technical skills, competency in AI and promote collaborative learning and team work spirit through multi -disciplinary projects and diverse professional activities.
    PEO3: apply competence and soft skills that allows them to contribute ethically to the needs of society and accomplish sustainable progress in the emerging computing technologies through life-long learning.

     

    Program Specific Outcomes (PSOs)

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    1. Students are able to analyze, implement, and deploy suitable AI & ML models across various domains
    2. Students are able to develop and use innovative tools and techniques to solve problems in the areas related to Deep Learning, Machine learning, Artificial Intelligence.

     

    Contact us

    Dr. D. RAVIKIRAN M.Tech, Ph.D
    professor & Head
    Department of AI & ML
    Mobile:7702875293
    E-mail: cjr.nettem@gmail.com