Bachelor of Technology

Robotics & Artificial Intelligence | B.Tech (RAI)

Robotics and Artificial Intelligence (AI) can transform Indian industries towards Industry-4.0 revolution. Manufacturing industry and supply chain organizations need to transform themselves towards digitization. The technological advancements worldwide have made it necessary for Engineers to have knowledge of Artificial Intelligence (AI) and Machine Learning (ML) for manufacturing and robotics systems. In order to accomplish this, we need to bridge the gap between Mechanical Engineering and Information Technology.

This hybrid program offers a journey from traditional manufacturing to smart manufacturing with IT as enabler. The degree offers a solid conceptual grounding in intelligent systems alongside the chance to apply knowledge in a practical setting, designing, building and testing robots. Areas of study may include: robot principles and design; software development; Internet of Things (IoT); robot intelligence control; AI and mobile robots; and operational management.

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Key Information


The Teaching-Learning-Evaluation (TLE) process is facilitated by faculty members with use of active learning strategies and ICT tools like DIY (Do-it-Yourself), Think Pair Share, use of learning management system (LMS – Moodle) etc.

Innovative assessment methods with a focus on handson learning are used by faculty members . Students gather a variety of learning experiences through pedagogy features, programming, simulations, models, peer learning, personalized adaptive learning, projects, internships and transform into industry-ready, competent Professionals.


  • Project-based learning

    A dedicated program to shape professionals with teaching focused on problem or project based learning

  • Internships

    Full time internship for six months in last year Sem - VIII along with opportunity for vacational internships

  • Knowledge beyond technical skills

    The program is enabled by expert faculties and guest lecturers from corporate to provide real-life examples to applicants

  • Rewarding career path

    Placement opportunities for eligible & interested students along with various domain opportunities like Smart Manufacturing, Machine Learning, Deep Learning, Expert Systems.

  • Interactive and active classroom sessions

    Simulations, animation, case study analyses, quizzes and lively discussion in the classroom, which enables students to learn the concepts most effectively


  • Open and Technical Electives

    Wide choice for branch specific electives and more number of open or interdisciplinary electives.


  • Dynamic and industry-oriented curriculum

    Focused curriculum with a rigor towards hands-on experience and industry exposure. The syllabus is designed in consultation with Industrial experts and academia, to address the current industrial and social needs. Facility Center with robotics lab, AI/ML lab etc.


Semester I Semester II
Course Group C Course Group C
Theory courses Theory courses
Applied Mathematics - I Applied Mathematics - II
Engineering Chemistry Engineering Physics
Engineering Drawing Engineering Mechanics
Elements of Electrical and Electronics Engineering  
Lab/Tutorial courses Lab/Tutorial courses
Python Programming Programming in C
Engineering Chemistry Laboratory Engineering Physics Laboratory
Elements of Electrical & Electronics Engineering Laboratory Engineering Mechanics Laboratory
Project-Based Learning Project-Based Learning
Basic Workshop Practice - I Presentation & Communication Skills
Engineering Drawing Laboratory Basic Workshop Practice - II
Exposure Course* Exposure Course*
Course Group P Course Group P
Theory courses Theory courses
Applied Mathematics - I Applied Mathematics - II
Engineering Physics Engineering Chemistry
Engineering Mechanics Engineering Drawing
  Elements of Electrical & Electronics Engineering
Lab/Tutorial courses Lab/Tutorial courses
Python Programming Programming in C
Engineering Physics Laboratory Engineering Chemistry Laboratory
Engineering Mechanics Laboratory Engineering Drawing Laboratory
Project-Based Learning Elements of Electrical & Electronics Engineering Laboratory
Presentation & Communication Skills Project-Based Learning
Basic Workshop Practice - I Basic Workshop Practice - II
Exposure Course* Exposure Course*

Note- Students will be assigned either course group C or P in semester I irrespective of their branch of study. Accordingly, they will have the other course group (P or C) in semester II

*mandatory non-credit course to be selected from a variety of courses from sports (indoor and outdoor), music, dance, creative art, culture, religion, yoga, broadcasting, film-making etc.

Semester III Semester IV
Applied Mathematics III Design of Machine Elements
Mechanics and Science of Materials Mechanics of Machines
Data structures and algorithms Mechatronics
Thermal Science and Engineering Fundamentals of Information Technology
Manufacturing process Data science
Semester V Semester VI
Robotics & Machine Vision Machine Learning
Operating systems Embedded Systems & IoT
Artificial Intelligence Big Data Analytics
Departmental Elective-I
  • Inspection and Quality Control
  • Design Thinking
  • Cloud Computing
  • Mind and Machine
Departmental Elective-II
  • Rapid Prototyping and Tooling
  • Operation Research
  • Search and Robotics
  • Machine Learning Foundation for Product Managers
Open Elective Technical (/NPTEL/SWAYAM/Coursera) Open Elective Technical/(*NPTEL/SWAYAM/Course era)
Open Elective Humanities Open Elective Management
  Mini Project
  MNCC-Business Communication
Semester VII Semester VIII
Smart Manufacturing Project-II /Internship
Departmental Elective-III
  • Smart Materials
  • Autonomous Vehicle
  • Computer Vision & Applications
  • Deep Learning
Departmental Elective - V /Online course
  • Sustainable Manufacturing
  • AR / VR
  • Quantum Computing
Departmental Elective-IV
  • AI product Management
  • UAV
  • Applications of ANN
  • Advance AI Techniques for the supply chain
  • Robotics: Mobility
Departmental Elective - VI/ online course
  • Supply Chain Analytics
  • Digital marketing
  • 3D Reconstruction-Multiple View points
Open Elective Technical  
Project – I  

Programme Outcomes

After successful completion of the program an Electronics Engineering Graduate will be able to:

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

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.

Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet specified needs with appropriate consideration for public health and safety and the cultural, societal, and environmental considerations.

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.

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.

The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, cultural, environmental, health, safety and legal issues relevant to the professional engineering practice; understanding the need of sustainable development.

Multidisciplinary competence: Recognize/ study/analyze/provide solutions to real- life problems of multidisciplinary nature from diverse fields

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

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

Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend & write effective reports and design documentation, make effective presentations and give and receive clear instructions.

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.

Lifelong 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.

Career Paths

  • Data Scientist
  • Big Data Engineer.
  • Machine Learning Engineer
  • Software Engineer
  • Automation Engineer
  • Public Sector Companies
  • Research and Design Engineer
  • Researcher & Academician
  • Administrative Services (IAS, IES)
  • IT Consultant
  • Business Analyst

Programme Specific Outcomes

After successful completion of the program Robotics and Artificial Intelligence Graduate will be able to:

Design, develop and implement complex robotic systems.

Exhibit expertise in advanced intelligent systems and applications.

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