M.Tech Artificial Intelligence Syllabus and Subjects 2024

Lisha Gupta

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. M.Tech AI course is a postgraduate course and therefore, provides students with all the vital information they need to succeed. The semester wise courses are as follows:

M.Tech AI First Year Syllabus
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

M.Tech AI Second Year Syllabus
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	__
Summer Internship	__

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
Modeling 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 artificial intelligence, computer science, 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.

M.Tech AI Books
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