ClinchWorks
Explore a subject, work through the curriculum, and choose your next step.
Fine-tune open-source language models efficiently on GPU infrastructure. Actual low-rank matrix optimization plus optional real PEFT and pretrained single-GPU workflows. Includes detailed lessons, worked solutions, failure injection, independent challenges and instructor assessment.
Understand and build interoperable tool/resource integrations using MCP concepts. An offline protocol-contract exercise plus optional real MCP SDK client/server integration. Includes detailed lessons, worked solutions, failure injection, independent challenges and instructor assessment.
Design multiple specialized agents only when decomposition adds measurable value. Bounded multi-worker coordination with synthetic evidence and explicit failure handling. Includes detailed lessons, worked solutions, failure injection, independent challenges and instructor assessment.
Compare major DevOps services across AWS, Microsoft Azure, Google Cloud, and Oracle Cloud Infrastructure. Design identity, networking, compute, storage, data, messaging, security, delivery, reliability, and cost controls through worked examples and local or paper labs, then justify a primary cloud and a second-cloud design.
Build a complete feed-forward neural network from scratch and understand the full training pipeline. Detailed engineering lessons with worked calculations, complete CPU labs, failure diagnosis, independent challenges and instructor capstone assessment.
Understand and implement the core mechanics of a neural network before using deep learning frameworks. Learn through explicit calculations, executable experiments, guided repairs and independently assessed changes.
