Title: What's Next
Course: AIINFRA 200: Production Inference Serving & GPU Orchestration > Section: Week 16 — Capstone Project & Course Review

🚀 What's Next

Congratulations on finishing AIINFRA 200: Production Inference Serving & GPU Orchestration. You now know how to take a trained model and turn it into a reliable, observable, cost-aware production service — a skill that sits at the center of nearly every real-world AI deployment. So where do you go from here? Your next course in the certificate path is AIINFRA 201: Model Adaptation — Fine-Tuning & Quantization. Where AIINFRA 200 focused on serving a model well, AIINFRA 201 turns to shaping the model itself — fine-tuning it for your use case and compressing it so it runs faster and cheaper. The two courses are natural partners: everything you learned here about GPU orchestration, quantization-aware serving, and capacity planning will make a lot more sense of why fine-tuning and quantization choices matter upstream — and vice versa. A few notes as you continue:

- You do not need to take a break to "reset" — the muscle memory from this course (containers, Kubernetes, GPU resource management) carries directly into AIINFRA 201's labs.
- If your capstone left you with an itch — a piece you wish you'd built out further — consider revisiting it once you've picked up fine-tuning and quantization skills. Several past students have turned their AIINFRA 200 capstone into a running project that evolves across the rest of the certificate.
- Keep an eye on your certificate progress in your student portal to confirm this course has been marked complete before you enroll in AIINFRA 201.

You've earned this. See you in the next course.

AIINFRA 200 · Production Inference Serving & GPU Orchestration

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