Module 1
AI foundations with a production lens
Build a clearer understanding of modern AI systems without getting trapped in purely theoretical coverage.
Youth Track
Applied AI programs for students and emerging builders who want real work before graduation
An applied AI learning pathway for university students and emerging builders who want production thinking, practitioner faculty, and practical work that goes beyond theory-heavy classroom learning.
Audience
University students, emerging builders, early-career technical talent
Format
Guided cohort, labs, community, applied projects
Built for specific operators, not for a generic AI audience
Every track is scoped around a role, a decision context, and the kind of work participants need to leave ready for.
Designed for serious learners early in their AI journey
Focuses on applied work, not certificate collection
Connects community, mentorship, and production thinking
Useful for universities, talent pathways, and emerging technical cohorts
What participants actually work through
Module 2
Applied labs and guided projects
Work through practical assignments and early-stage projects that begin shaping a real AI portfolio.
Module 3
Practitioner exposure
Learn from faculty still building in the field and get a clearer sense of what serious AI work actually looks like.
Module 4
Career and capability direction
Use the cohort to understand which path fits best next: builder depth, flagship growth, or enterprise-aligned technical work.
You're a fit if...
Students who want more than a surface-level AI course
Emerging builders looking for practical structure and direction
University cohorts that want stronger industry proximity
This is not for you if...
Learners looking for a no-effort credential
Participants uninterested in hands-on assignments or guided projects
Advanced builders who already need deep production specialization
How the track runs in practice
The outcome is not just attendance. Each track is designed to change decision quality, engineering capability, or institutional readiness.
Structured but demanding
The track is designed to be accessible, but it still expects discipline, attendance, and active participation.
Community-led energy
It carries forward the academy’s Chandigarh.AI roots: peer learning, public energy, and practical curiosity.
Pathway-oriented
The goal is not just completion. The goal is to prepare participants for their next serious move.
What this track is meant to change
Outcome 1
A stronger base for future builder or flagship progression
Outcome 2
Applied work that is more defensible than generic classroom exercises
Outcome 3
Clearer direction on how to keep building after the cohort
Practitioner faculty across leadership, build, and governance
Faculty Director
Dr. Jagreet Kaur Gill
AI and Decision Intelligence · Agentic Enterprise Strategy
Leads the academic direction of XDFE with a focus on translating enterprise AI ambition into operating models, decision systems, and production strategy.
Builder Track Lead
Suryakant Tomar
Agentic AI · GenAI Engineering · Multi-Agent Systems
Works at the engineering edge of applied AI systems, helping builders move from experimentation into dependable agentic and multi-agent delivery.
Architect Track Lead
Chandan Gaur
AI Governance · EU AI Act · Sovereign AI Policy
Guides governance, standards, and sovereign AI thinking for institutions that need rigorous strategy, compliance alignment, and long-term operating control.
Leadership Track Lead
Riya Khurana
Applied AI Literacy · Adaptive Leadership · Responsible AI
Helps senior leaders build AI fluency, responsible deployment judgment, and the confidence to lead transformation without relying on abstract theory.
Explore the adjacent pathways in the academy
If youth track is the right fit, start the conversation now
We can route you into the right cohort, advisor workflow, or admissions path based on your role, region, and goals.