M.Tech in Artificial Intelligence and Robotics is a postgraduate program that is gaining popularity due to the growing demand for skilled professionals in the field of AI and Robotics. Here are some of the highlights of the program.
It is a post-graduate programme that focuses on providing advanced knowledge and skills in the fields of artificial intelligence and machine learning. The programme covers topics such as machine learning, natural language processing, neural networks, computer vision, robotics, deep learning, data analysis and more.
Name of the Program: M.Tech in Artificial Intelligence and Robotics
Duration of the Program: 2 years
Stream | Engineering |
Course | M.Tech. Artificial Intelligence And Robotics |
Full Name | MASTER OF TECHNOLOGY IN ARTIFICIAL INTELLIGENCE AND ROBOTICS |
Eligibility | Graduation |
Duration | 2 Years |
Fees | 100000 |
Type | Degree |
Mode | Year |
Candidates must have a Bachelor's degree in Computer Science, Electronics and Communication, or any related field with a minimum of 50% marks.
Typically, candidates must have a bachelor's degree in a relevant field such as Computer Science, Electrical Engineering, Electronics and Communication Engineering, Mechanical Engineering, or related disciplines. Some universities may require a specific minimum percentage or grade point average (GPA) in undergraduate studies.
Universities usually announce the commencement of the admission process through their official website or advertisement in newspapers or online platforms. The notification contains important details such as application deadlines, eligibility criteria, and required documents.
Many universities conduct entrance exams for admission to M.Tech. programs, such as the Graduate Aptitude Test in Engineering (GATE) in India. Candidates need to register for these exams separately and obtain a valid score within the specified cutoff to be eligible for admission.
Interested candidates need to fill out the application form provided by the university. This form may be available online or in hard copy format. Applicants must ensure that they provide accurate information and submit all required documents along with the application form.
Candidates are selected on the basis of their performance in the entrance exam, followed by a personal interview.
Entrance Exam: GATE, TANCET, etc.
Letters of Recommendation: Some institutions may require letters of recommendation from professors or employers who can vouch for the candidate's academic abilities, work ethic, and potential for success in the program.
Statement of Purpose (SOP): Applicants may need to submit a statement of purpose outlining their academic background, career goals, reasons for choosing the program, and how they plan to contribute to the field of artificial intelligence and robotics.
Interviews: In some cases, candidates may be required to attend an interview as part of the admissions process. This interview may assess the candidate's suitability for the program and provide an opportunity to discuss their academic and professional background.
Candidates can apply for the program through the official website of the respective colleges or universities.
The application fee varies from one college to another.
Syllabus: The syllabus for the M.Tech in Artificial Intelligence and Robotics program includes subjects like Machine Learning, Robotics, Natural Language Processing, Computer Vision, etc.
Graduates of this program can work as Machine Learning Engineers, Robotics Engineers, Artificial Intelligence Specialists, Data Scientists, etc. Graduates can work in research institutions, universities, or private companies involved in advancing the field of artificial intelligence and robotics. They may contribute to developing new algorithms, technologies, and applications that push the boundaries of AI and robotics capabilities.
Many companies require AI and robotics experts to develop software and applications that leverage machine learning, computer vision, natural language processing, and other AI techniques. Graduates can work as software engineers, AI developers, or machine learning engineers in industries such as technology, healthcare, finance, and manufacturing.
With expertise in robotics, graduates can pursue careers in designing, developing, and maintaining robotic systems for various purposes, including industrial automation, healthcare, agriculture, and space exploration. Roles may include robotics engineer, automation engineer, or systems integration specialist.
The average salary for a professional with an M.Tech in Artificial Intelligence and Robotics degree is around INR 7-8 lakhs per annum.
Here is the step-by-step process to apply for the M.Tech in Artificial Intelligence and Robotics program:
Step 1: Check the eligibility criteria of the college or university where you wish to apply.
Step 2: Register for the entrance exam (GATE, TANCET, etc.) and appear for it.
Step 3: Check the result of the entrance exam and apply for the program on the official website of the college or university.
Step 4: Fill the application form with all the necessary details and upload the required documents.
Step 5: Pay the application fee online.
Step 6: Submit the application form.
After the submission of the application form, the college or university will conduct a personal interview of the candidates who have qualified the entrance exam. The final selection is based on the performance of the candidate in the entrance exam and the personal interview.
Foundations of Artificial Intelligence (AI):
Introduction to artificial intelligence
Problem-solving and search algorithms
Knowledge representation and reasoning
Planning and decision-making
Introduction to machine learning
Machine Learning:
Supervised learning algorithms (e.g., linear regression, logistic regression, support vector machines)
Unsupervised learning algorithms (e.g., clustering, dimensionality reduction)
Deep learning fundamentals (neural networks, backpropagation)
Convolutional neural networks (CNNs) for computer vision
Recurrent neural networks (RNNs) for sequential data
Robotics:
Introduction to robotics and robot components
Kinematics and dynamics of robot manipulators
Robot motion planning and control
Robot perception (sensors, computer vision)
Robot localization and mapping (SLAM - Simultaneous Localization and Mapping)
Natural Language Processing (NLP):
Introduction to NLP and its applications
Text preprocessing and feature extraction
Language modeling and sequence-to-sequence learning
Named entity recognition, sentiment analysis, and text classification
Neural network-based approaches for NLP tasks
Computer Vision:
Image processing techniques (filters, transformations)
Feature extraction and image representation
Object detection and recognition
Image segmentation and scene understanding
Deep learning for computer vision (CNN architectures, transfer learning)
Reinforcement Learning:
Introduction to reinforcement learning
Markov Decision Processes (MDPs)
Value iteration and policy iteration
Q-learning, SARSA, and temporal difference learning
Deep reinforcement learning and applications
Human-Robot Interaction (HRI):
Introduction to HRI and its importance
Design principles for human-friendly robots
Gesture recognition and speech interaction
Social robotics and affective computing
Ethical considerations in HRI
Research and Development
Software Development
Robotics Engineering
Autonomous Vehicles
Healthcare Applications
Natural Language Processing (NLP)
Data Science and Analytics
Consulting and Advisory Roles
Entrepreneurship