Google AI Studio
30-day exploration of Google AI Studio — Gemini API, model playground, grounding, and real-world agent workflows.
Course Content
Phase 1 — Foundations
Understand what Google AI Studio is, what it can do, and get your bearings in the interface.
Phase 1 — Foundations
Write your first effective prompt and understand the difference between bad prompts and great ones.
Phase 1 — Foundations
Understand the Gemini model family — which model to use when, and why it matters for cost and quality.
Phase 1 — Foundations
Master the model parameters — temperature, top-p, top-k, max tokens. Stop leaving them on defaults.
Phase 1 — Foundations
Unlock the power of system instructions — the most underused feature in AI Studio.
Phase 1 — Foundations
Understand chat vs single-turn prompts vs structured prompts — and when to use each.
Phase 1 — Foundations
Week 1 capstone — build a reusable prompt template library and understand prompt versioning.
Phase 2 — The API
Get your API key, make your first real API call, and understand the auth model.
Phase 2 — The API
Use the Python SDK to call Gemini cleanly — your primary development interface.
Phase 2 — The API
Use the JavaScript/Node.js SDK — essential for web apps and integrations.
Phase 2 — The API
Send images to Gemini — unlock true multimodal AI.
Phase 2 — The API
Analyse PDFs and documents with the Files API — unlock document intelligence.
Phase 2 — The API
Get structured JSON output from Gemini — the key to building reliable applications.
Phase 2 — The API
Implement streaming responses — the difference between a frozen app and a responsive one.
Phase 3 — Advanced Features
Master function calling — connect Gemini to real-world tools and APIs.
Phase 3 — Advanced Features
Enable Google Search grounding — give Gemini access to real-time, factual web data.
Phase 3 — Advanced Features
Exploit the 1M token context window — the most powerful feature most people don't use.
Phase 3 — Advanced Features
Understand and use embeddings for semantic search — the foundation of intelligent retrieval.
Phase 3 — Advanced Features
Use Gemini's code execution tool — let the AI run Python to get exact answers.
Phase 3 — Advanced Features
Implement context caching — save money and speed up repeated large-context calls.
Phase 3 — Advanced Features
Understand safety settings and content filters — configure them for your use case.
Phase 4 — Building Real Apps
Design and implement a multi-turn chat agent with memory and context.
Phase 4 — Building Real Apps
Build a RAG (Retrieval Augmented Generation) pipeline — the foundation of knowledge-based AI apps.
Phase 4 — Building Real Apps
Understand Google AI Studio vs Vertex AI — when to graduate to enterprise infrastructure.
Phase 4 — Building Real Apps
Master rate limits, costs, and quotas — the unsexy skills that make production apps work.
Phase 4 — Building Real Apps
Process audio and video with Gemini — the full multimodal toolkit unlocked.
Phase 4 — Building Real Apps
Build a complete full-stack AI application — from backend API to frontend UI.
Phase 4 — Building Real Apps
Evaluate and test your Gemini prompts — the discipline that separates guesswork from engineering.
Phase 5 — God Mode
Build a multi-agent system — orchestrate multiple AI models working together.
Phase 5 — God Mode
Graduation: ship your signature AI system, define your path forward, and understand what's next.