Program Highlights

• Practical Learning & Industry Integration : This program mingle theoretical knowledge with Hands-on experience with tools like Tensor Flow, Py-Torch, AWS, and Tableau. Solve industry-sponsored problems (e.g. predictive healthcare models, autonomous systems). Annual AI/ML challenges with global participation. Combines mathematics, statistics, and domain knowledge to design intelligent systems.
• Future-Ready Curriculum: Designed with input from leading tech companies. Integrate interdisciplinary knowledge (e.g., mathematics, statistics) into AI-driven solutions. Focuses on AI techniques (e.g., neural networks, NLP, computer vision) and ML algorithms (e.g., regression, clustering, deep learning).Address ethical, social, and security challenges in AI/ML deployment. Collaborate effectively in teams and communicate technical ideas to wide range of people.

• Project-Based Learning: Capstone projects, hackathons, and internships with industry partners. Partnerships with tech leaders for workshops, live projects, and mentorship. Apply foundational computer science concepts to design software and systems. Develop AI/ML models to analyze data, automate tasks, and enhance decision-making. Graduates gain expertise to work in high-demand roles like AI Engineer or Data Scientist.
• Industrial Aligned Opportrunities: Collaborate on faculty-led projects in robotics, NLP, or AI ethics. Access GPU clusters, robotics kits, and high-performance computing facilities. Equips graduates to work with emerging technologies like generative AI, robotics, and quantum computing. Work on futuristic projects like autonomous drones, personalized healthcare, or smart cities. Opportunities to collaborate with international research labs or tech hubs.