M.tech in Machine Learning is a pioneering and specialized postgraduate program that delves deep into the heart of one of the most transformative technologies of our time. In an era where data has become the lifeblood of innovation and artificial intelligence is reshaping industries, this program equips students with the knowledge, skills, and expertise to harness the power of machine learning.
Machine learning, a subfield of artificial intelligence, is the driving force behind applications that range from virtual personal assistants and recommendation systems to autonomous vehicles and predictive healthcare diagnostics. The M.Tech in Machine Learning stands at the forefront of this technological revolution, offering a comprehensive understanding of the principles, algorithms, and practices that underpin this dynamic field.
This program is designed to empower students to become proficient in the art of teaching machines to learn, adapt, and make intelligent decisions. It covers a wide spectrum of topics, including supervised and unsupervised learning, deep learning, natural language processing, computer vision, and reinforcement learning. Students also explore the ethical and responsible deployment of machine learning, ensuring they are equipped to navigate the complex landscape of AI ethics.
Candidates who have completed their Bachelor of Technology (B.Tech) or Bachelor of Engineering (B.E) from an accredited institution with a minimum aggregate score of 50% are eligible for admission to the M.Tech in Machine Learning program. This requirement ensures that applicants have a strong foundation in the relevant field, equipping them with the essential knowledge to excel in the program.
Admission to the M.Tech program in Machine Learning primarily depends on academic qualifications and performance in a mandatory entrance examination. The Graduate Aptitude Test in Engineering (GATE) is widely recognized as the primary and most prestigious qualifying exam among several entrance tests accepted by leading institutions. A strong GATE score not only demonstrates a candidate’s expertise in the subject but also plays a crucial role in securing admission to reputable universities. It is, therefore, a crucial step in the application process for this specialized and highly competitive field of study.
Why Choose the M.Tech in Machine Learning?
A compelling array of reasons underpins the decision to pursue a Master of Technology (M.Tech) in Machine Learning, making it an intriguing choice for people with a penchant for cutting-edge technology and a thirst for knowledge. Here are some crucial reasons to think about:
- Technology Pioneering: A M.Tech in Machine Learning places you at the forefront of technological innovation. Machine learning is at the heart of the most recent advances in artificial intelligence, data analysis, and predictive modeling
- Machine Learning Experts in great Demand: In an era driven by data, machine learning specialists are in great demand across a wide range of businesses. Organizations are looking for people who can extract insights from data, create predictive models, and optimize decision-making processes.
- Diverse Career Opportunities: With this degree, you can pursue a variety of careers. Among the many jobs available are machine learning engineer, data scientist, AI researcher, and data analyst. Because of this variety, you can design your profession to your interests.
- Innovation and Research: M.Tech in Machine Learning allows you to get involved in research, development, and innovation. You’ll work on ground-breaking projects, create sophisticated algorithms, and help push technology forward.
- Ethical AI Development: The curriculum emphasizes ethical AI development, ensuring that you obtain not only the technical abilities but also the ethical awareness needed for responsible AI deployment.
- Problem Solving with Data: Machine learning gives you the skills you need to solve complicated problems using data. Whether it’s improving healthcare, boosting corporate operations, or addressing environmental challenges, you’ll be prepared to make a difference.
- Interdisciplinary Knowledge: The program includes supervised learning, deep learning, natural language processing, and computer vision. This multidisciplinary approach provides you with a diverse skill set.
- Global Collaboration: Many M.Tech programs in Machine Learning draw students from all around the world. This multicultural setting encourages collaboration, exposes you to new viewpoints, and broadens your global network.
- Personal Satisfaction: If you are excited about the potential of AI and want to contribute to the development of intelligent systems, an M.Tech in Machine Learning can be both personally and academically enjoyable.
- Competitive Advantage: An M.Tech in Machine Learning sets you apart in a competitive work market. Your advanced academic background in machine learning reflects your commitment to excellence and preparedness to tackle tough problems.
Highlights
| Aspect | Description |
| Degree | M.tech in Machine Learning |
| Duration | Typically 2 years of full-time study |
| Eligibility | Bachelor of Technology (B.Tech) or Bachelor of Engineering (B.E) from a recognized institution with a minimum of 50% aggregate marks |
| Admission Criteria | Primarily based on merit and performance in a qualifying entrance exam (e.g., GATE), |
| Entrance Exams | GATE 2023, TANCET 2023, AP PGECET 2023, SRMJEEE PG 2023, VITMEE 2023, JNU CEE M.Tech 2023, CUCET Engineering 2023, BITS HD Admission Test 2023, Karnataka PGCET 2023, TS PGECET 2023IIIT Delhi M.Tech Entrance Exam 2023, Gujarat PGCET 2023, OJEE PG 2023, ISI Admission Test 2023, WBUT PGET 2023, MET PG 2023, IPU CET M.Tech 2023, GITAM GAT PGTA 2023, LNMIIT M.Tech Admission 2023, IIITM-K PG 2023, JIIT PGET 2023 |
| Career Opportunities | Artificial Intelligence Research Companies, Robotics companies Coordinating Committee for Artificial Intelligence, etc |
| Courses Fees | Rs. 1,00,000/- to Rs. 2,50,000/- Per Annum |
| Average Starting Salary | Rs. 3,00,000/- to Rs. 9,50,000/- Per Annum |
| Top Institutes | IITs, NITs, and Leading Engineering Colleges |
Syllabus
First Year
| Semester I | Semester II |
| Advanced Engineering Mathematics | Finite Element Methods in Engineering |
| Advanced Mechanics of Solids | Optimization Methods in Engineering |
| Mechanical Vibration | Fracture, Fatigue and Failure Analysis |
| Advanced Machine Design | Rotor Dynamics and Condition Monitoring |
| Finite Element Methods | Rotor Dynamics |
| Analytical Dynamics | Mechanical Behaviour of Materials |
| Design with Advanced Engineering Materials | Polymers and Composite Materials |
| Control and Instrumentation | Computer-Aided Design and Analysis |
Second Year
| Semester III | Semester IV |
| Project Work Phase I | Project Work Phase II |
| Program Elective 1 | Program Elective 2 |
Subject
| ore Subjects | Lab Subjects | Elective Subjects |
| Electrical and Electronics | Circuits-Signal Conditioning Processes | Fracture Mechanics |
| Fastening and Joining | Types of Amplifiers | Computational Fluid Dynamics |
| Fluid Power | Lowpass and HighPass Filters | Industrial Noise Control |
| Manufacturing | – | Experiments B – Robotics |
| Engineered Materials | – | Industrial Training |
| Mechanical Engineering | – | – |
| Motion Control | – | – |
Average Fees
| Courses | Average Fees |
| M.tech in Machine Learning | Rs. 1,00,000/- to Rs. 2,50,000/- Per Annum |
Eligibility Criteria
| Criteria | Description |
| Qualification | Bachelor’s degree in Engineering or Technology (B.E./B.Tech) in a relevant field from a recognized university or institution. |
| Academic Performance | Typically, candidates should have a minimum aggregate score of 55% to 60% in their undergraduate degree. Some institutions may have specific grade point average (GPA) requirements. |
| Entrance Exam | Many M.Tech programs require candidates to qualify in a national or state-level entrance exam, such as GATE (Graduate Aptitude Test in Engineering). The exam score is a significant factor in the admission process. |
| GATE Score Cutoff | Different M.Tech programs may have specific GATE score cutoffs for various categories (General, OBC, SC/ST). Meeting the minimum cutoff is essential for admission. |
| Work Experience (if any) | Some institutions may consider work experience as an additional eligibility criterion, particularly for part-time or sponsored M.Tech programs. |
| Relaxation for SC/ST/OBC | Universities often provide relaxation in eligibility criteria for candidates belonging to Scheduled Castes (SC), Scheduled Tribes (ST), and Other Backward Classes (OBC). |
| Non-GATE Admissions | In cases where candidates haven’t taken the GATE exam or haven’t secured a qualifying score, some institutions may admit students based on a written test and interview. |
Entrance Exams for M.Tech Courses
| Exam | Conducting Authority |
| GATE 2023 | Jointly conducted by IIT Bombay, Delhi, Guwahati, Kanpur, Kharagpur, Madras, Roorkee and the Indian Institute of Science (IISc) Bangalore |
| TANCET 2023 | Anna University |
| AP PGECET 2023 | Andhra University |
| SRMJEEE PG 2023 | SRM Institute of Science and Technology |
| VITMEE 2023 | VIT University |
| JNU CEE M.Tech 2023 | Jawaharlal Nehru University (JNU) |
| CUCET Engineering 2023 | Central Universities Common Entrance Test (CUCET) |
| BITS HD Admission Test 2023 | Birla Institute of Technology and Science (BITS) |
| Karnataka PGCET 2023 | Karnataka Examination Authority |
| TS PGECET 2023 | Osmania University |
| IIIT Delhi M.Tech Entrance Exam 2023 | Indraprastha Institute of Information Technology (IIIT) |
| Gujarat PGCET 2023 | Admission Committee for Professional Courses (ACPC) |
| OJEE PG 2023 | Odisha Joint Entrance Examination Board |
| ISI Admission Test 2023 | Indian Statistical Institute (ISI) |
| WBUT PGET 2023 | West Bengal University of Technology (WBUT) |
| MET PG 2023 | Manipal Academy of Higher Education |
| IPU CET M.Tech 2023 | Guru Gobind Singh Indraprastha University (GGSIPU) |
| GITAM GAT PGTA 2023 | Gandhi Institute of Technology and Management (GITAM) |
| LNMIIT M.Tech Admission 2023 | The LNM Institute of Information Technology |
| IIITM-K PG 2023 | Indian Institute of Information Technology and Management – Kerala |
| JIIT PGET 2023 | Jaypee Institute of Information Technology (JIIT) |
Career opportunities for M.Tech in Machine Learning
| Career Opportunity | Description | Average Annual Salary (in Rupees) |
| Machine Learning Engineer | Develop and implement machine learning models and algorithms. | ₹6,00,000 – ₹20,00,000 |
| Data Scientist | Analyze data, create predictive models, and derive insights. | ₹7,00,000 – ₹18,00,000 |
| Artificial Intelligence Research Scientist | Conduct advanced AI research in academia or industry. | ₹8,00,000 – ₹20,00,000 |
| Natural Language Processing Engineer | Work on language-related AI applications and models. | ₹6,00,000 – ₹15,00,000 |
| Computer Vision Engineer | Develop computer vision solutions for various industries. | ₹7,00,000 – ₹18,00,000 |
| Data Engineer | Manage data pipelines, databases, and optimize data workflows. | ₹6,00,000 – ₹15,00,000 |
| AI Product Manager | Lead the development of AI-driven products and services. | ₹10,00,000 – ₹25,00,000 |
| Robotics Engineer | Design and build robotic systems with AI capabilities. | ₹7,00,000 – ₹18,00,000 |
| Machine Learning Consultant | Provide expert guidance on AI strategy and implementation. | ₹8,00,000 – ₹20,00,000 |
| AI Ethicist | Ensure ethical AI development and responsible AI usage. | ₹7,00,000 – ₹18,00,000 |
Top Colleges For M. Tech in Machine Learning
| College | Location | Fees (in Lakhs) |
| Annamalai University | Annamalai Nagar, Tamil Nadu | ₹2.15 Lakhs |
| DAIICT Gandhinagar | Gandhinagar, Gujarat | ₹2.68 Lakhs |
| IIIT Bhagalpur | Bhagalpur, Bihar | Not specified |
| IIIT Pune | Pune, Maharashtra | ₹9.23 Lakhs |
| IIST Thiruvananthapuram | Thiruvananthapuram, Kerala | ₹1.67 Lakhs |
| IIT Guwahati | Guwahati, Assam | Not specified |
| IIT Kharagpur | Kharagpur, West Bengal | ₹45.85 Lakhs |
| JIIT Noida | Noida, Uttar Pradesh | ₹3.25 Lakhs |
GATE Engineering Predicators
Engineering predictors are essential tools that utilize historical data and algorithms to assess a student’s potential rank or admission chances in M.Tech programs, especially when seeking admission based on the Graduate Aptitude Test in Engineering (GATE) scores. These predictors offer valuable insights into the likelihood of securing admission to specific M.Tech courses or institutions, streamlining the admission process.
Our suite of predictors includes:
- GATE Rank Predictor
- GATE College Predictor
GATE Counseling Expert
As experts in M.Tech admissions, we also provide specialized support and guidance for students navigating the admission process. Our team of knowledgeable Engineering Admission Consultants is well-versed in the GATE counseling process, dedicated to helping students achieve their academic and career aspirations in the field of M.Tech. Whether it’s selecting the right college, preparing applications, or understanding the counseling procedure, our Engineering Admission Consultants are here to ensure a smooth and seamless journey for aspiring M.Tech students.
GATE Expert Counselling
Our expert counseling services extend to GATE-based admissions, whether you aspire to enter prestigious institutions like IITs or other renowned engineering colleges offering M.Tech programs. We also provide guidance for state-level counseling processes, ensuring that you receive personalized assistance to make informed decisions throughout the admission process.
Our M.Tech admission support includes:
- GATE Counseling
- Top Engineering Colleges
- State-Level Counseling
Frequently Asked Question
Q1. What is M.Tech in Machine Learning?
A. M.Tech in Machine Learning is a specialized postgraduate program that focuses on the study and application of machine learning techniques, a subfield of artificial intelligence, to solve complex problems using data and algorithms.
Q2. Who is eligible for an M.Tech in Machine Learning?
A. Typically, candidates who have completed a Bachelor of Technology (B.Tech) or Bachelor of Engineering (B.E) in a relevant field with a minimum specified aggregate are eligible. Admissions may also require a qualifying exam like GATE (Graduate Aptitude Test in Engineering).
Q3. What are the core subjects covered in this program?
A. Core subjects often include supevised learning, unsupervised learning, deep learning, natural language processing, computer vision, and more. These subjects provide a strong foundation in machine learning principles and practices.
4. Are there practical components to the program?
A. Yes, M.Tech in Machine Learning often includes lab work, where students apply theoretical knowledge to real-world problems, develop algorithms, and gain hands-on experience with machine learning tools and technologies.
Q5. What are the career opportunities after completing M.Tech in Machine Learning?
A. Graduates can pursue careers as machine learning engineers, data scientists, AI researchers, natural language processing engineers, and more. The demand for machine learning experts is high in various industries.
Q6. Do I need to have programming skills to excel in this program?
A. While it’s beneficial to have programming skills, M.Tech programs often provide training in programming languages such as Python, which is widely used in machine learning.
Q7. What is the duration of an M.Tech in Machine Learning program?
A. Typically, the program is two years long, including coursework, practical work, and possibly a thesis or project.
Q8. How competitive is the job market for M.Tech in Machine Learning graduates?
A. The job market for machine learning professionals is competitive due to the high demand for their skills. Graduates with strong knowledge and practical experience often find promising career opportunities.
Q9. What is the research scope in this field?
A. M.Tech in Machine Learning can be a stepping stone to research opportunities in AI and machine learning. Graduates interested in research can pursue Ph.D. programs or engage in advanced research projects.
Q10. How does this program address ethical considerations in machine learning?
A. Many M.Tech programs include courses on ethics in AI, ensuring that students are aware of the ethical implications of their work and the responsible development of AI systems.