Students explore AI tools through new centre of excellence

NIIT University has launched an Artificial Intelligence Centre of Excellence to provide students, faculty members and research scholars with access to computing infrastructure and tools for AI-related learning and research.

The centre is designed to support practical work in areas such as machine learning, deep learning, generative AI, edge AI, agentic AI and data-intensive research. Students will have opportunities to work with AI models and explore stages including training, fine-tuning and deployment as part of academic projects and research activities.

The facility is equipped with three YodaEdge devices and can support up to 30 concurrent users. Its technology environment includes NVIDIA systems and tools, along with platforms such as PyTorch and JupyterLab.

For students, the centre provides a setting to complement classroom learning with practical experimentation. Areas of application include computer vision, natural language processing, large language models, intelligent Internet of Things systems, predictive analytics and smart healthcare.

The centre will also support activities such as technical workshops, faculty development programmes, hackathons and industry interaction sessions.

These activities are intended to give students opportunities to work on different types of AI problems and understand how computational tools are applied beyond theoretical coursework.

Prof Prakash Gopalan, President, NIIT University, said the centre would support experiential learning by giving students access to AI computing infrastructure during their academic programmes.

The facility is part of the university’s broader focus on AI and interdisciplinary learning. Students can use the infrastructure for coursework, projects and research, while faculty and research scholars can use it for experimentation and collaborative work.

The centre is expected to support projects involving generative AI applications, retrieval-augmented generation (RAG), multimodal AI, robotics and perception systems, model optimisation and human-computer interaction.

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