M.Tech. in Artificial Intelligence & Machine Learning
A two-year specialized program focusing on deep learning, neural networks, and AI-driven solutions. Ideal for students aiming to build careers in AI research, robotics, and automation.
Associate Partner – HVET
Course Highlights
Advanced AI & ML Curriculum
Internship linked to Job
Big Data & AI Integration
Hands-on Learning
Certification from Intel & Nasscom
Industry & Research Collaboration
Cutting-Edge Tools & Frameworks
NEP & SDG Aligned
Placement & Career Support
Tools Covered
Introduction
- Master of Technology (MTech) in Artificial Intelligence & Machine Learning is a cutting-edge program designed for professionals and students who aspire to master AI-driven innovations, deep learning techniques, and intelligent system development. With industries rapidly integrating AI solutions, this program equips students with the technical expertise and problem-solving skills required to build and deploy AI models at scale.
- The course blends theoretical foundations with hands-on applications, covering machine learning algorithms, neural networks, natural language processing (NLP), and computer vision. Students will gain practical exposure to real-world AI challenges, working on industry projects, research collaborations, and AI-powered automation solutions.
- With the increasing demand for AI specialists across technology, healthcare, finance, robotics, and autonomous systems, this program ensures graduates are industry-ready for high-impact roles in AI research, development, and deployment.
Eligibility
Passed Bachelor’s Degree or equivalent. Obtained at least 50% marks (45% marks in case of candidates belonging to reserved category) in the qualifying examination.
Duration
2 Years Full-Time (4 Semesters)
Tuition Fees
Rs. 70000 /- Per Semester
*Fees such as Admission, Caution Money, Examination, Hostel, and Transport fees are extra
Program Details
MTech in Artificial Intelligence & Machine Learning is a 2-year postgraduate program focused on advanced AI methodologies, deep learning frameworks, and data-driven decision-making.
The course allows students to specialize in key areas such as reinforcement learning, generative AI, AI for robotics, explainable AI (XAI), and AI ethics.
Disciplined Approach – The program follows a structured curriculum with regular research assessments, AI project reviews, and real-world AI case studies.
Qualitative Approach – The course emphasizes hands-on experimentation, industry internships, AI-driven hackathons, and expert-led AI innovation workshops.
Program Outcome
Mastering AI & ML Algorithms
Develop expertise in supervised and unsupervised learning, deep learning architectures, and AI model optimization.
Building Scalable AI Solutions
Gain hands-on experience in AI model deployment, cloud-based AI systems, and large-scale AI applications.
Understanding AI Ethics & Governance
Learn responsible AI development, bias detection, AI fairness, and data privacy regulations.
Developing AI for Real-World Applications
Work on AI-driven solutions for healthcare, finance, cybersecurity, robotics, and autonomous systems.
Harnessing AI with Emerging Technologies
Leverage AI integration with IoT, blockchain, quantum computing, and edge AI.
Encouraging Research & Innovation
Engage in AI research, publications, and patent-driven innovations to push the boundaries of AI technology.
Industry-Ready AI Expertise
Prepare for high-demand careers as AI engineers, research scientists, AI architects, and data scientists in global tech industries.
Course at a Glance
Core Subjects: Math for AI, Adv. DSA, Deep Learning, NLP, Computer Vision, RL, AI Security, Ethical AI, Cloud & Edge AI, AI Robotics & IoT.
Specialized Areas: AI in Healthcare, Finance, Smart Cities, Quantum AI, Business Intelligence
Skill Training: AI Lab Internships, Capstone Projects, Hackathons, Research & Innovations, Industry Collaborations.
Outcome: Expertise in AI-driven solutions for cutting-edge research, automation, and industry applications.