IIIT Delhi Launches Networks for AI/ML Systems Course on AI Fabrics and Systems

The Indraprastha Institute of Information Technology Delhi (IIIT Delhi) has launched an advanced academic course titled "Networks for AI/ML Systems" focusing on AI fabrics and systems; a specialised area where networking, memory hierarchies and distributed execution impact the performance of large-scale artificial intelligence and machine learning infrastructure.

The programme has been introduced in collaboration with the Indian affiliate of Marvell Technology, Inc., with contributions from industry practitioners and ongoing mentoring from technical experts.

About the Course

• Title: Networks for AI/ML Systems
• Institution: IIIT Delhi
• Partner: Indian affiliate of Marvell Technology, Inc.
• Focus: AI networking fabrics, memory systems, distributed execution and high-performance machine-learning infrastructure

The course is designed to train students on aspects of AI system design and performance optimisation that are rarely covered in traditional AI/ML programmes. It emphasises the systems layer of modern AI, including how data movement, memory hierarchies and network fabrics influence large-scale performance and scalability.

Industry-Academia Collaboration

The new programme is co-designed and co-taught by faculty from IIIT Delhi and industry experts:

• Dr. Rinku Shah - Faculty, IIIT Delhi
• Abed Mohammad Kamaluddin - Director, Marvell Technology (Indian affiliate)
• Marvell engineers and architects; Technical mentors for the course

This collaboration reflects a growing trend in Indian tech education where academic institutions and industry partners jointly develop specialised courses, combining foundational knowledge with real-world systems experience.

Why It Matters

Experts at IIIT Delhi describe the programme as one of the first of its kind in India and possibly globally. By integrating AI networking, CXL-based memory systems, AI-scale simulation and distributed training insights, the course aims to fill a gap in existing AI/ML curricula that typically focus more on algorithms and models rather than the underlying system infrastructure.

Around 45 students from BTech, MTech and PhD programmes participated in the initial cohort, with hands-on projects and peer-driven learning reported to significantly strengthen student understanding of complex AI systems behaviour.

Industry and Research Outlook

In addition to coursework, IIIT Delhi and Marvell are collaborating on joint research efforts in AI networking and systems, helping strengthen India's position in advanced computing, AI infrastructure and semiconductor capabilities; areas aligned with national priorities in technology innovation.

The programme is expected to build a cohort of professionals and researchers equipped to tackle system-level challenges in AI, preparing them for roles in industry sectors where AI infrastructure expertise is increasingly crucial.

Who Should Consider This Course

This programme is suitable for students and professionals who:

• Have a technical background in computing or electrical engineering
• Want to specialise in system-level aspects of AI/ML
• Are interested in careers related to AI infrastructure, distributed computing, hardware-software co-design or advanced machine learning systems

While detailed eligibility and application details are controlled by IIIT Delhi, interested candidates are expected to meet the institute's academic criteria and follow the official admission process as published on the institute's portal.

Bottom Line

With the launch of Networks for AI/ML Systems, IIIT Delhi and Marvell have taken a significant step toward bridging academic theory and real-world AI infrastructure needs, equipping future engineers with specialised skills that are increasingly in demand as AI systems scale and deepen in industry and research applications.