Turn official tutorials into a practical learning path
From Google Gemini and OpenAI GPT to Claude, Hugging Face, and Azure OpenAI. Every guide keeps the official source visible and adds implementation order, safety boundaries, and business exercises.
Google Gemini API Quickstart: From AI Studio to Your First Request
A practical companion to Google's official quickstart: create a key, protect it, make a text request, and turn the prototype into a maintainable app.
Read tutorialGPT API Quickstart: Build a Reliable Minimum Loop with OpenAI's Guide
Do not start with a complex agent. Secure the key, call the Responses API, handle failures, then add structured outputs and tools one layer at a time.
Read tutorialGPT Prompt Engineering: Turn Good Chat into an Evaluable Workflow
Prompting is not magic phrasing. Use clear tasks, references, constraints, examples, and evals to turn a lucky answer into a repeatable workflow.
Read tutorialClaude API Getting Started: From the First Message to Reliable Long-Context Work
Use Anthropic's official getting-started path to understand the Messages API, system prompts, long inputs, and tool boundaries.
Read tutorialThe Hugging Face LLM Course: From Model Calls to Your Own Evaluation Set
Do not reduce an open-model course to copying a notebook. Build transferable foundations from tokenizers and pipelines to pre-fine-tuning evaluation.
Read tutorialAzure OpenAI Quickstart: Put GPT Behind Enterprise Access and Monitoring
The Azure version is about more than calling a model: resources, deployment names, identity, networking, and logs matter when a prototype becomes an enterprise service.
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