Executive M.Tech in Artificial Intelligence & Machine Learning
Admission Closed
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Course Duration:
2 Years
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Mode of Learning:
Online + Campus Immersion
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Program Fee:
₹ 3,40,000
Program Overview
The Executive M.Tech in Artificial Intelligence & Machine Learning is designed for working professionals seeking deeper academic grounding and applied expertise in modern AI systems.
Delivered over four semesters and comprising 80 credits, the programme establishes strong foundations in mathematical modelling, machine learning algorithms, and intelligent system design. As learners progress, they gain advanced exposure to Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, and Big Data platforms supporting AI applications.
The curriculum integrates research methodology, responsible AI practices, and specialised electives, ensuring a balanced development of theoretical depth and implementation capability. The programme culminates in a guided project or dissertation, enabling participants to apply AI/ML techniques to real-world challenges and scalable systems.
Program Eligibility
- Applicants must hold a B.E./B.Tech. in Engineering or an MCA/MSc (in Physics, Mathematics Statistics, CS, IT, DS, or related fields) or an equivalent degree.
- A minimum of 60% or a 6.0 CPI on a 10-point scale (or equivalent) in the qualifying degree is required.
- The program is designed for working professionals, and while specific work experience requirements may vary, a background in the IT industry is highly recommended.
Who Are These Programs For?
Software engineers and developers transitioning into AI-driven roles
Data analysts and data scientists seeking deeper algorithmic and modelling expertise
AI/ML practitioners looking to formalise and advance their academic credentials
Technology professionals working on intelligent systems, automation, and predictive analytics
Professionals aspiring to contribute to research, advanced model development, or enterprise AI implementation
Key Benefits of the Program
Position yourself for senior roles in AI engineering, data science, and intelligent systems development
Apply research-backed methodologies to solve complex, high-impact business challenges
Design scalable machine learning pipelines ready for real-world deployment
Develop the capability to build, evaluate, and optimise deep learning models
Build the confidence to lead AI-driven initiatives within your organisation
Skills You Will Gain
Natural Language Processing
Technical Collaboration
Research & Analysis
Big Data Handling
Reinforcement Learning
Deep Learning Design
Program Objectives
Advanced AI & ML Capability
Develop in-depth knowledge and expertise in Artificial Intelligence and Machine Learning to solve complex real-world problems.
Strategic & Leadership Readiness
To prepare graduates for leadership roles that require data-driven thinking and AI-led innovation.
Research & Continuous Advancement
To cultivate analytical thinking and continuous learning aligned with evolving AI technologies.
Ethical AI Understanding
To build awareness of responsible AI practices and societal implications in system deployment.
Interdisciplinary Collaboration
To enable effective communication and teamwork across technical and business functions.
Scalable AI System Design
To equip professionals with the skills required to design and deploy robust AI/ML solutions at scale.
Program Highlights
Institute of National Importance
Graduate with a nationally recognised M.Tech in Artificial Intelligence & Machine Learning.
Academic Depth with Applied Relevance
Develop a strong theoretical foundation while building implementation capability.
Exposure to Emerging AI Specialisations
Explore Generative AI, MLOps, Edge AI, and Scalable Machine Learning systems.
Research-Driven Learning Experience
Undertake a structured dissertation or capstone project that demonstrates applied problem-solving capability.
Distinguished Faculty
Learn from experienced faculty combining academic excellence with industry insight.
On-Campus Immersion
Participate in immersive academic sessions that encourage collaboration and interaction.
Executive Alumni Status
Become part of the IIIT Vadodara alumni network and strengthen professional connections.
Collaborative Peer Ecosystem
Engage with a cohort of professionals enabling multidisciplinary knowledge exchange.
Program Outcomes
- Strong Mathematical & Engineering Foundations
Develop the ability to apply mathematics, science, and core engineering principles to the design, analysis, and optimisation of AI and Machine Learning systems. - Experimental Design & Analytical Thinking
Gain the capability to design structured experiments, analyse complex datasets, and interpret results within AI and ML environments. - Real-World AI System Design
Build solutions that address practical requirements while considering economic, ethical, environmental, social, safety, and sustainability factors.
- Cross-Functional Team Effectiveness
Work efficiently within multidisciplinary teams contributing to AI-driven projects and system implementation. - Structured Problem-Solving in AI & ML
Identify, formulate, and resolve engineering challenges across Artificial Intelligence and Machine Learning domains. - Professional Integrity & Ethical AI Practice
Demonstrate an understanding of professional standards and ethical responsibility in the development and deployment of AI technologies.
Tools You'll Work With
Course Structure
Semester I
| Course Code | Course Name |
|---|---|
| EMAI101 | Big data platforms for AI & ML |
| EMAI102 | Advanced Data Structures & Algorithms |
| EMAI103 | Mathematical Foundations for AI (Linear Algebra, Probability, Optimization) |
| EMAI104 | Programming for AI & Data Science (Python, NumPy, Pandas, Scikit-learn) |
| EMAI105 | Foundations of Machine Learning |
Semester II
| Course Code | Course Name |
|---|---|
| EMAI201 | Deep Learning |
| EMAI202 | Natural Language Processing |
| EMAI203 | Research Methodology & AI Ethics |
| EMAI204 | Computer Vision |
| EMAI205 | AI/ML Strategy and Business Value Creation |
Semester III
| Course Code | Course Title |
|---|---|
| EMAI301 | Reinforcement Learning & Decision Intelligence |
| EMAI302 | Elective-1 |
| EMAI303 | Elective-2 |
| EMAI304 | Elective-3 |
| EMAI305 | Elective-4 |
Semester IV
| Course Code | Course Title |
|---|---|
| EMAI401 | Elective-5 |
| EMAI402 | Elective-6 |
| EMAI403 | Project Work / Research + Dissertation |
Elective Pool
| Elective Pool - 3 from each pool - Mandatory | ||
|---|---|---|
| Sr no | Advanced AI / ML Engineering & Deployment | AI for Business Transformation & Strategy |
| 1 | Scalable Deep Learning and Distributed Training | AI Driven Business Model Innovation |
| 2 | MLOps Automation and Orchestration | Digital Transformation with AI/ML |
| 3 | Generative AI: Customization and Deployment of LLMs | AI for Competitive Advantage and Market Intelligence |
| 4 | High-Performance Computing for AI/ML | AI in Supply chain and Operations Optimization |
| 5 | Embedded AI and Edge Machine Learning | AI in Finance ( Fin Tech) |
| 6 | Emerging Trends in AI/ML and Future of AI | AI Governance, Policy and Compliance |
| 7 | Probabilistic Graphical Models | AI in Retail and E- Commerce |
| 8 | Scalable Model Serving and Inference Optimization | Crisis Management & Business Continuity in ICT |
Fee Structure
| Fees Components | Sem I | Sem II | Sem III | Sem IV |
| Application Fee (One Time) | 1,000 | - | - | - |
| Caution Deposit (Refundable) | 10,000 | 10,000 | - | - |
| I Card Fee (One time) | 100 | - | - | - |
| Tuition Fee | 85,000 | 85,000 | 85,000 | 85,000 |
| Campus Immersion Fee (optional) | 3,000 | - | - | - |
| Institute Registration Fees | 1,000 | 1,000 | 1,000 | 1,000 |
| Alumni Fee | 1,000 | 1,000 | 1,000 | 1,000 |
| Convocation Fee | 1,000 | 1,000 | 1,000 | 1,000 |
| Total | 1,03,600 | 98,000 | 89,500 | 88,000 |
Admission Process
Online Application
Document Verification
Acknowledgement
Payment of Application Fees
(Non Refundable)
Payment of Admission Fees
Program Coordinator
Prof. -
Associate Professor
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FAQs
- What is the M.Tech in Artificial Intelligence and Machine Learning
program?
The M.Tech in Artificial Intelligence and Machine Learning is an advanced postgraduate program designed to build deep expertise in modern AI technologies, machine learning algorithms, and large-scale data systems. The program prepares professionals to design, develop, and deploy intelligent systems across industries. - How does the program help professionals advance their careers?
By completing the M.Tech in Artificial Intelligence for working professionals, learners gain advanced technical capabilities in AI, data science, and machine learning systems, enabling them to move into specialised engineering, research, and technology leadership roles. - Who should pursue this Executive M.Tech in Artificial Intelligence?
The Executive M.Tech in Artificial Intelligence is ideal for:
• Working professionals in software, data, or technology roles
• Engineers looking to transition into AI and machine learning domains
• Professionals seeking advanced expertise in data-driven technologies.
It is structured to support career advancement while continuing professional responsibilities. - Is a GATE score required to apply for this program?
No, a GATE score is not mandatory for admission to this Executive M.Tech in Artificial Intelligence program. Applicants who already have a valid GATE score may submit it during the admission process if they wish, but it is not a compulsory requirement for eligibility. - Can I continue working while pursuing this online M.Tech in Artificial
Intelligence?
Yes. The program is structured to support flexible learning, allowing professionals to pursue the online M.Tech in Artificial Intelligence while continuing their professional responsibilities. - Will I receive a degree upon successful completion of the program?
Yes. Upon successfully completing all academic requirements, participants will receive a Master of Technology (M.Tech) in Artificial Intelligence and Machine Learning from the Indian Institute of Information Technology Vadodara, an Institute of National Importance known for its academic excellence and research in advanced computing and emerging technologies.