M.Tech in AI and ML is a postgraduate program that focuses on artificial intelligence, machine learning, and data science. The program equips students with the skills and knowledge required to design, develop, and deploy AI and ML applications.
M.Tech. in Artificial Intelligence and Machine Learning at SIT Pune is a 2 years course offered at the PG level. To get admitted to M.Tech. in Artificial Intelligence and Machine Learning course at SIT Pune, applicants must meet the entry requirements - 50.0% in graduation. The total tuition fee for SIT Pune M.Tech. in Artificial Intelligence and Machine Learning is INR 370000. Apart from the tuition fee, there is a one-time admission fee of - INR 20000, and a hostel fee of amount INR 409000 that students are required to pay.
Stream | Engineering |
Course | M.Tech. AI And ML |
Full Name | Master Of Technology In AI And ML |
Eligibility | Graduation |
Duration | 2 Years |
Fees | 50000 |
Type | Degree |
Mode | Year |
The entrance exam for M.Tech in AI and ML
L varies depending on the university or institute. Some of the popular exams include GATE, JAM, and JEE.
Students can get admission to the M.Tech in AI and ML program based on their performance in the entrance exam and their academic qualifications.
Universities or institutions usually announce the commencement of the admission process through their official website or other mediums. The notification includes important details such as application deadlines, eligibility criteria, and required documents.
Interested candidates need to fill out the application form provided by the university or institution. 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.
To be eligible for M.Tech in AI and ML, candidates must have a bachelor's degree in engineering or technology with a minimum of 60% marks.
candidates must have a bachelor's degree in a relevant field such as Computer Science, Electronics and Communication Engineering, Electrical Engineering, Information Technology, Mathematics, or related disciplines from a recognized university or institution. Some universities may require a specific minimum percentage or grade point average (GPA) in undergraduate studies.
Some universities may require candidates to have a valid score in national or university-level entrance examinations. For example, in India, the Graduate Aptitude Test in Engineering (GATE) is a commonly accepted entrance exam for M.Tech. programs. Candidates need to check the specific requirements of each university or institution regarding entrance exams.
The duration of the M.Tech in AI and ML program is typically two years.
The selection criteria for M.Tech in AI and ML includes the candidate's performance in the entrance exam, academic qualifications, and interview.
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 Machine Learning.
Interview (if applicable): In some cases, universities may conduct interviews as part of the admission process, especially for highly competitive programs or to assess the suitability of candidates. The interview may be conducted in person, over the phone, or through video conferencing.
Students can apply for M.Tech in AI and ML online or offline depending on the institute's application process.
Gather all the necessary documents required for the application process. Typical documents may include:
Academic transcripts and degree certificates
Entrance exam scorecard (if applicable)
Letters of recommendation (if required)
Statement of Purpose (SOP)
Resume/CV
English language proficiency test scores (for international students)
The application form for M.Tech in AI and ML is available online on the institute's website.
To apply for M.Tech in AI and ML, students must fill out the application form, pay the application fee, and submit the required documents.
The fee for M.Tech in AI and ML varies depending on the institute. On average, the fee ranges from INR 2-4 lakhs per year.
The syllabus for M.Tech in AI and ML includes subjects like machine learning, deep learning, data mining, natural language processing, and computer vision.
Foundations of Artificial Intelligence:
Introduction to AI: history, goals, and applications
Intelligent agents: agents, environments, and agent types
Problem-solving methods: search algorithms, heuristic search, and optimization techniques
Machine Learning Fundamentals:
Introduction to machine learning: types of learning, supervised vs. unsupervised learning
Linear algebra and calculus for machine learning: vectors, matrices, derivatives
Probability and statistics for machine learning: probability distributions, statistical inference, hypothesis testing
Supervised Learning Algorithms:
Linear regression and polynomial regression
Logistic regression
Decision trees and ensemble methods (bagging, boosting, random forests)
Support Vector Machines (SVM)
k-Nearest Neighbors (k-NN)
Neural networks and deep learning fundamentals
Unsupervised Learning Algorithms:
Clustering algorithms: K-means, hierarchical clustering, DBSCAN
Dimensionality reduction techniques: Principal Component Analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE)
Association rule mining: Apriori algorithm
Reinforcement Learning:
Introduction to reinforcement learning: Markov Decision Processes (MDPs), policy, reward, value functions
Dynamic Programming: policy evaluation, policy iteration, value iteration
Monte Carlo methods
Temporal Difference learning: Q-learning, SARSA
Deep reinforcement learning: Deep Q-Networks (DQN), Policy Gradient methods
Natural Language Processing (NLP):
Introduction to NLP: tasks and challenges
Text preprocessing techniques: tokenization, stemming, lemmatization
Word embeddings: Word2Vec, GloVe
Named Entity Recognition (NER)
Sentiment analysis, text classification, and topic modeling
Computer Vision:
Introduction to computer vision: image representation, feature extraction
Image classification and object detection algorithms: Convolutional Neural Networks (CNNs), region-based CNNs (R-CNN), YOLO
Image segmentation techniques: semantic segmentation, instance segmentation
Object tracking and image generation
Advanced Topics:
Generative Adversarial Networks (GANs)
Reinforcement learning for robotics
Transfer learning and domain adaptation
Federated learning and privacy-preserving machine learning
Explainable AI and interpretable machine learning
Graduates of M.Tech in AI and ML can get jobs as data scientists, machine learning engineers, AI engineers, and research scientists. The starting salary for M.Tech in AI and ML graduates ranges from INR 5-10 lakhs per annum.
They work with large datasets, implement machine learning pipelines, and deploy models into production systems. Salary: $90,000 - $150,000 per year.
They use statistical techniques, machine learning algorithms, and data visualization tools to uncover patterns and trends in data. Salary: $95,000 - $160,000 per year.
They work in academia, research institutions, or industry R&D labs. Salary: $100,000 - $180,000 per year.
Deep Learning Engineers specialize in designing and implementing deep neural network architectures for applications such as computer vision, natural language processing, and speech recognition. Salary: $100,000 - $160,000 per year.
Machine Learning Engineer
Data Scientist
AI Research Scientist
Deep Learning Engineer
AI Consultant
Research Scientist (Industry)
AI Product Manager
Data Engineer
M.Tech in AI and ML graduates can work in industries like healthcare, finance, retail, e-commerce, and manufacturing. They can also work in research and development in universities and research institutions.
Machine Learning Engineers design and develop machine learning models and algorithms to solve complex problems.
Data Scientists analyze and interpret large volumes of data to extract actionable insights and drive decision-making processes.
AI Research Scientists conduct research to advance the field of artificial intelligence, develop new algorithms, and solve challenging problems.
Research Scientists in industry conduct applied research to develop new products, technologies, or solutions.