The M.Tech AI syllabus can be divided into four semesters. It covers topics such as technologies to various study components such as Graph Theory, Electronics System Design, Introduction to Robotics, Embedded Systems and many more. Experience in task performance is also provided. The course, along with core subjects in the semester, even includes other specializations for further skill development.

Semester wise M.Tech AI Syllabus

The M.Tech AI course consists of core and elective subjects. Depending on the university/college, they may differ slightly. It has two parts -a compulsory set of courses covering all foundation areas in mathematics and many elective courses that aim to build job-specific skills and knowledge. The semester wise courses are as follows:

Semester I

Semester II

Graph Theory

Robot Programming

Electronics System Design

Electrical Actuators and Drives

Introduction to Robotics

Image Processing & Machine Vision

Machine and Mechanics

Robotics Based Industrial Automation

Embedded Systems

Robotics Control System

Manufacturing System Simulation

Principles of Computer Integrated Manufacturing

Semester III

Semester IV

Artificial Intelligence and Neural Network

Comp Numerical Control Machines & Adaptive Control

System modelling and identification

Manufacturing Systems Automation

Nano Robotics

Robot Economics

Robot Vision

Modern Material Handling Systems

Robotic Simulation

Group Technology and Cellular Manufacturing

PLC and Data Acquisition system

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Summer Internship

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M.Tech AI Subjects

The M.Tech AI subjects taught in the course are mostly similar for all the colleges, depending on the institution's course module. But, the overall subjects are quite similar but put in a different order, depending on the teaching method. Overall, the course makes them have a peculiar way of learning and gives an Experience in training in management, analytics, and commerce.

Core Subjects:

  • Advanced-Data Structures And Algorithms
  • Mathematics For Artificial Intelligence
  • Foundations Of Artificial Intelligence
  • Foundations Of Data Science
  • Statistical Learning Theory
  • Probabilistic Graphical Models
  • Optimization Techniques
  • Reinforcement Learning

Elective Subjects:

  • Foundation of Data Science
  • Machine Learning
  • Multi-Agent Systems
  • Living labs
  • Modelling and Simulation
  • AI in Natural Language Processing
  • Introduction to Game Theory

M.Tech AI Course Structure

The M.Tech AI course syllabus is designed to mainly include various systems of food science, production, and analysis. This provides knowledge and skills to deal with the technicalities and diverse issues with food processing technologies and many more. This field sharpens a student's mind to tackle the daily obstacles faced in their workplace, studies & other similar aspects. The course involves subjects which include aspects like

  • Practical/Record
  • Core Subjects
  • Elective Subjects
  • Seminar/Research
  • Internship

M.Tech AI Teaching Methodology and Techniques

M.Tech AI is a course focusing on different aspects of Intelligence, computer and technology. The course is designed based on requirements and helps get the most exposure to the field, and the MTech course subjects deal with the same. Learning strategies have varying implications for courses.

  • Assignments/Viva-voce
  • Following course module books
  • Research work
  • Internships

M.Tech AI Projects

M.Tech AI project, known as a mini-thesis, is a compulsory project for the students to complete at the end of their semester. Students should regard their projects as an ideal opportunity to integrate what they have learned during the M.Tech program and apply it to their future working profession.

Some of the project topics are

  • Facial Emotion Detection using Neural Networks.
  • Online Logistic Chatbot System
  • Lane-Line Detection System in Python using OpenCV.
  • Voice-based Intelligent Virtual Assistant for Windows.
  • Cancer Prediction using Naive Bayes
  • Transformer Conversational Chatbot in Python using TensorFlow 2.0.

M.Tech AI Reference Books

MSc course is the one meant for the specialization in the field of Computer. The topics taught in the course module are very much enough. But, to get a deep or in-depth knowledge, there are certain books published by the -authors, who have opened up about their thought process, and thus helps in being more skilled and knowledgeable about the course which is a major part of M.Tech AI Subjects.

Name

Author 

Playing Atari with Deep Reinforcement Learning

Mnih, Volodymyr

Digital Image Processing

. R. C. Gonzalez, R. E. Woods

“Intellectual Property in New Technological Age

Robert P. Merges, Peter S. Menell, Mark A. Lemley

Insight into Data Mining: Theory and Practice

. K. P. Soman, V. Ajay and DiwakarShyam

Machine Learning, a Probabilistic Perspective

Kevin P. Murphey

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