Frontier Tech · Advanced
Edge AI & Embedded Intelligence
Localized intelligence for factories, vehicles, retail and robots: model compression, edge hardware, on-device agents and fleet MLOps — where latency, privacy and physics rule.
The centre of gravity for inference is moving to the edge: factory lines, vehicles, stores and robots increasingly run models locally for latency, privacy, resilience and cost. This program trains engineers to ship intelligence onto constrained hardware — quantisation and distillation, accelerator selection, on-device language and vision models, and the fleet-scale MLOps that keeps thousands of deployed devices observable, updatable and safe.
Who it's for
Embedded, platform and ML engineers; IoT and manufacturing-systems teams. C/C++ or Python required.
Tools & stack
What you'll walk away with
- Select edge hardware and accelerators against real workloads
- Compress models: quantisation, pruning, distillation with quality gates
- Deploy on-device vision and language models with local fallbacks
- Design fleet MLOps: OTA updates, telemetry, drift detection
- Build privacy-preserving architectures that keep data on site
Curriculum
01Edge fundamentals
- Latency, privacy, resilience economics
- Accelerator landscape
- Power and thermal budgets
- Lab: baseline benchmark
02Model engineering
- Quantisation and distillation
- Small language models on device
- Vision pipelines at the edge
- Lab: compressed model deploy
03Fleet operations
- OTA update strategies
- Telemetry and drift detection
- Fail-safe and offline design
- Lab: fleet dashboard
04Capstone
- Edge architecture defence
- Cost and privacy review
- Production checklist
- Certification
Pricing
Value-based
Two-part: a one-time enablement fee plus a per-seat rate that falls as the cohort grows.
Indicative rate card · ≈ ₹9,499/hr · $250/hr
Seats limited
Choose a cohort
New cohort dates announced weekly — enrol now and pick your dates with an advisor.
Pay by PO · nothing upfront · net 30 days · GeM & tender-ready
Or reserve a seat online
₹9,499deposit
Reserves your seat & dates. Balance invoiced per your engagement.
Secure · Razorpay · full refund 7+ days before start
Every enrolment includes
- • Qube copilot access throughout
- • All session recordings & materials
- • Graded applied project with review
- • Verifiable certificate on completion
- • 30-day post-programme support
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