Honours in AI, Computer Vision and Robotics

Electronics Engineering | B.Tech. (ETRX)

Artificial Intelligence (AI), Computer vision and Robotics honour program gives a broad perspective of modern technologies and applications in real life. AI, when combined with robotics, allows users to build smart robots that can work independently as per inputs from robotic sensors. Artificial Intelligence and Robotics allows theory, algorithms, and systems for making intelligent decisions in complex and uncertain environments.

The course covers most aspects of artificial intelligence and robotics including perception and interpretation of sensor data, learning about environments, learning to make decisions, automated planning and reasoning, and interaction of AI robotic systems with each other and with humans. The computer vision when added to smart robotics gives true problem-solving solutions in industrial environments. Computer vision with artificial intelligence trains computers to interpret and understand the visual world. Machines can accurately identify and locate objects then react to what they “see” using digital images from cameras, videos, and deep learning models. After completing this Honours degree students will be equipped with knowledge from all the three domains and will be industry ready in true sense.

Objectives

The program aims to:

  • Apply intelligent process automation with the help of Robotic Process Automation, Artificial Intelligence and Machine learning technologies.
  • Assist the students to understand computer vision including the interfacing of camera and image processing to enhance detection and object recognition.
  • Understand the interfacing of the robotic systems to AI and complete the task using kinematics, path planning, and tool movements with minimum time and in an efficient way.

Learning Outcomes

At the successful completion of this Honor program, students will able to

  • LO1: Apply core concepts of AI, computer vision and robotics to real world problems.
  • LO2: Explore advanced computer vision and machine learning approaches for industrial applications.

Eligibility Criteria

Students who have passed the First Year of Engineering in Electronics Engineering successfully.

Assessment Method

Laboratory performance evaluation, Mini Projects, Viva-voce, Online Quiz, Continuous Assessment through internal assessments and unit tests, End Semester Examination.

List of Courses

  • Modern Artificial Intelligence
  • Advanced Computer Vision
  • Applied Robotics
  • Intelligent systems
  • Project on AI, Robotics, and computer vision/ Internship *

    (* Internship of 4 weeks or more approved by the department)

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