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    Today the AI has become very popular worldwide. The era is known as era of Artificial Intelligence. AI is simulation of natural intelligence in machines that has the capability to think, mimic and execute tasks like human. It is continuously growing area. It can be applied in various sectors like healthcare, agriculture, retail, transportation, banking, oil and gas etc. for different purposes. Data Science and Machine learning are the branches of AI which learns from data finds patterns and makes decisions. Some examples of Artificial Intelligence include self-driving cars, computers that play chess, credit card fraud detection, automation, and robotics to help farmers to find out more effective ways to protect their crops from weeds.

    Levels of Awards/Exit Points



    B.Tech. Artificial Intelligence & Data Sciences

    4 Year



    Engineering Graduates will be able to: 

    1)      PO1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

    2)      PO2: 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.

    3)      PO3: 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)  PO4: 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)      PO5: 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)      PO6: 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)      PO7: 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.

    8)      PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

    9)      PO9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

    10)   PO10: 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)  PO11: 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)  PO12: 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. 


    PSO 1: Understand, analyze, and develop innovative solutions for real world problems in industry and research establishments related to Artificial Intelligence and Data Science

    PSO 2:Ability to develop skills to address and solve social and environmental problem with ethics and perform multidisciplinary projects with advance technologies and tools.


    For the practical exposure of students following LABS are the important parts of their course curriculum:
    1.      LAB on Data Structure Using C
    2.      LAB on Discrete Structure and Logic
    3.      LAB on Computer Organization & Architecture
    4.      LAB on Operating System
    5.      LAB on Python
    6.      LAB on Microprocessor
    7.      LAB on Artificial Intelligence
    8.      LAB on Machine Learning
    9.      LAB on Data sciences



       ·         The department provides certification for CCNA through SMS CISCO Networking Academy.
    ·         Students get to know about cloud services using Microsoft’s Azure DevOps.
    ·         Runs Employability Enhancement Program (EEP) for all around personality and soft-skill development
    ·         Hands on training on advance courses like PHP, Python, Machine Learning, Android, Ethical Hacking and IOT etc.
    ·         Continuous National and International guest lectures from academia and corporate world.
    ·         Voluntary participation of students in regular PowerPoint presentations on current topics.
    ·         Mock interviews, seminars, webinars, and workshops on various topics.
    ·         Special focus on innovation and research through major and minor industrial projects.


    ·         HTML & JAVA SCRIPT

    ·         ASP.NET

    ·         Android & Advanced Java

    ·         Summer Internship Project

    ·         Python

    ·         Machine Learning and Artificial Intelligence

    ·         Internet of Things

    ·         Minor Project

    ·         Major Project


    ·         Workshops

    ·         Guest Lectures

    ·         Industrial Visit.

    ·         Seminars

    ·         Live Projects

    Course Outecome:

    B.Tech AI&DS Course Outcome


      B.Tech AI&DS 1st Year   B.Tech AI&DS 2nd Year



    Contact No.

    Email ID

    Mr. Sunit Kumar Mishra



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