About CoDE-AI

The Competitive Data Engineering and Artificial Intelligence (CoDE-AI) is a student group supported by the Infosys Center for Artificial Intelligence (CAI) with the goal of establishing a thriving ecosystem of skilled, well-trained, industry and research ready, ML/AI engineers. We are looking for participation from passionate and enthusiastic students who are interested in the broad area of AI, and have a knack for getting their hands dirty with code and data!!

Students can be in any program and in any year and choose to be a part of CoDE-AI. The prerequisites for being a member is simply a drive for developing AI/ML and/or Data Engineering solutions that could potentially tackle challenging, real-world problems.

Following are the expectations from the student members of CoDE-AI:

1. Participate in some AI/ML data challenges organized at various top-tier AI/ML conferences and workshops.

2. Contribute in designing and developing new AI/ML tools and customizing existing tools to solve real-world problems that CAI members are working on. These contributions could be in research or in engineering or both.

3. Gain experience with the entire AI pipeline - Data Engineering & Data Science, AI/ML algorithms, and MLOps / ML Engineering.

4. Have fun exploring the exciting field of AI/ML and share your learnings with other members.


Note: For 1. and 2. above, Students would get mentorship from CAI members (Faculty, senior PhD scholars, RAs, etc.) and dedicated compute resources.


Following are the direct benefits of participating in CoDE-AI.

1. Access to high-end computing servers for working on projects aligned with interest of CAI faculty members

2. Access to CAI infrastructure - trained SoTA models across various different domains, inference code, engineering tricks for training models, debugging and analysis tools.

3. Access to practical know-how through seminars and interactions - We will have regular seminars by both in-house experts as well as external experts, who will help us learn the latest tricks for training a variety of models, debugging them and negotiating deployment challenges.

4. Access to opportunities for working on real-world AI projects - CoDE-AI is envisioned to become the go-to place for AI-related projects at IIITD (and beyond!). With skilled students at CoDE-AI, state-of-the-art hardware and software infrastructure, we foresee a diverse set of AI projects opportunities being announced at CoDE-AI.

5. Learn ML while you are having fun!