A student-centric transformation programme is being launched to integrate next-generation AI and agentic AI into degree programmes, curricula, laboratories, projects, and learning activities, preparing learners to understand, develop, and deploy autonomous AI systems.

Students will move from AI tool users to creators, gaining exposure to AI, ML, Generative AI, LLMs, and related technologies, with a focus on planning, reasoning, database and application integration, and context-aware workflow execution.

Senior officials from HCL Group and KL Deemed to be University attended the signing ceremony, highlighting a strategic industry-academia collaboration to embed AI across the learning ecosystem.

The initiative promotes an AI product-building mindset, guiding learners through problem identification, data prep, development, testing, deployment, and continuous improvement via industry-led challenges, hackathons, and competitions.

Project-based learning will tackle challenges across sectors such as healthcare, education, agriculture, manufacturing, finance, retail, cybersecurity, smart cities, HR, and supply chains, using industry-led problems and research projects.

Industry-aligned, project-based learning is designed to drive functional AI solutions across multiple sectors, accelerating practical applications of AI.

Promising teams may advance prototypes to market-ready products or startups, opening careers like AI Engineer, Agentic AI Developer, Generative AI Engineer, ML Engineer, LLM Application Developer, AI Automation Engineer, and AI Product Engineer.

Successful prototypes could become market-ready products or startups, enabling graduates to pursue diverse AI-focused roles.

The programme aims to bridge gaps between academic learning and industry expectations, fostering innovation and real-world AI solutions.

Leaders including the Chancellor and the Dean emphasise embedding AI across the learning ecosystem to produce industry-ready professionals who can design, deploy, and responsibly use intelligent technologies.

The programme emphasizes hands-on experiences in prompt engineering, Retrieval-Augmented Generation, multimodal applications, intelligent chatbots, AI copilots, enterprise assistants, intelligent search, workflow automation, and AI-enabled decision-support, alongside strengthening software engineering skills.

Program specifics include hands-on exposure to these AI techniques and reinforced software engineering capabilities in programming, full-stack development, cloud computing, databases, DevOps, cybersecurity, and deployment.