What You’ll Learn
A deep dive into the **final mile of AI engineering**—designed by NanoSchool’s Deep Science Learning Organisation under NSTC guidelines for advanced practitioners ready to ship models that scale.
Model Serialization
Save models in ONNX, TorchScript, or SavedModel formats for portability.
API Design
Build FastAPI endpoints with Pydantic validation, async, and batching.
Model Serving
Deploy with TorchServe, TensorFlow Serving, and Docker containers.
AI to Production
Add logging, Prometheus metrics, health checks, and Kubernetes autoscaling.
Who Should Enroll?
For ML engineers and AI developers in India—especially in Delhi NCR—who have trained models but need to **deploy them reliably at scale**.
- ML engineers at Indian AI startups
- Computer vision/NLP developers building APIs
- Research engineers transitioning to production roles
- Technical leads managing model delivery pipelines
Hands-On Projects
Fraud Detection API
Serve a PyTorch model via FastAPI with request validation and rate limiting.
Vision Model Server
Deploy a ResNet using TorchServe with batch inference and health monitoring.
Capstone
Full Model Serving System
End-to-end system reviewed by NSTC mentors—with Docker, metrics, and load testing.
3-Week Syllabus
Total: ~36 hours • Lifetime LMS access • Delhi NCR GPU lab support
Week 1: Model Packaging & APIs
- ONNX, TorchScript, SavedModel
- FastAPI with Pydantic schemas
- Lab: Build a sentiment analysis API
Week 2: Production Serving
- TorchServe handlers & config
- TensorFlow Serving REST/gRPC
- Lab: Containerize a vision model
Week 3: Scaling & Monitoring
- Prometheus + Grafana dashboards
- Kubernetes deployment & HPA
- Capstone: Load-test your serving system
NanoSchool LMS & NSTC Mentorship
Access **GPU-enabled cloud labs** and lifetime LMS resources. Get direct feedback from mentors certified by the NanoSchool Technology Council (NSTC)—many with experience deploying models at Indian fintech, healthtech, and AI startups.
NSTC-Accredited Certificate
Verified by the NanoSchool Technology Council (NSTC). Shareable on LinkedIn. Recognized by Indian employers and startups in Delhi NCR.
Frequently Asked Questions
Do I need to know Docker or Kubernetes?
Basic Docker knowledge is helpful but not required—we teach it in context. Kubernetes is introduced at a practical level (deployment YAML, HPA), not from scratch.
Will we cover cloud platforms (AWS/GCP)?
We focus on **cloud-agnostic serving**. The same Dockerized models can be deployed on AWS SageMaker, GCP Vertex AI, or on-prem—skills transfer directly.
Is this just about APIs?
No. We go beyond simple APIs to **production-grade serving**: batching, health checks, metrics, scaling, and observability—what Indian AI teams actually use in production.
