IIIT Delhi Offers Students a Chance to Master AI: 40-Hour Course Launched

New AI Course at IIIT Delhi: Indraprastha Institute of Information Technology (IIIT Delhi) has launched a specialized AI course for BTech and MTech students, focusing on next-generation artificial intelligence technologies. Here’s what students need to know about this 40-hour program.

AI Fabrics and Systems Course:
IIIT Delhi, in collaboration with Marvel Technology Inc.’s Indian branch, has introduced a new program titled Networks for AI/ML Systems. The 40-hour course focuses on AI fabrics and systems, combining advanced academic knowledge with industry insights. It is designed to prepare students for roles in research and industry, covering advanced computing infrastructure, system architecture, production-level AI infrastructure, and next-generation AI platform development.

Who Can Enroll?
The program has been designed and is taught by Dr. Rinku Shah and Marvel’s Director Abed Mohammad Kamaluddin. Students also receive continuous technical mentoring from Marvel engineers and architects. The course is offered as an elective within the BTech and MTech curriculum. Around 45 students from BTech, MTech, and PhD programs have already participated in the inaugural batch.

Student Projects:
Prof. Pushpendra Singh, Head of IIIT Delhi’s Computer Science and Engineering Department, said this is India’s first course on networks for AI/ML systems. Student projects include AI fabrics and transport, CXL-aware training and inference, distributed training and serving pipelines, in-network compute, telemetry-driven optimization, and ML-based security and observability.

Admission and Course Duration:
Eligibility requires students to be enrolled in IIIT Delhi’s BTech or MTech programs. The Networks for AI/ML Systems course runs for one semester, totaling 40 hours, with 3 hours of classes per week.

Career Scope:
Upon completing the course, students can pursue careers in AI data centers in research and engineering roles. Graduates may work on designing high-performance networks, AI fabrics, and scalable systems capable of supporting large-scale AI/ML workloads.