Gemini & Google AI
A deep, hands-on mastery path for Gemini: models and the app, Gems, Workspace, Extensions, AI Studio and the Gemini API, Gemini CLI and Code Assist, agents, Vertex AI, automation, and a capstone.
Everyone talks about Google AI. You are going to run it. This block takes you from the Gemini model family all the way to a production workflow you actually ship, and it does not waste your time on theory you will never use.
Start with fundamentals: when pro earns its keep and when flash wins, how gems and personalization make Gemini yours, and why multimodality and long context are the superpowers that change how you work. Then you put it to work inside Google Workspace, in docs, gmail, sheets, slides, meet, drive, and the side panel, with the governance and data controls a serious leader has to answer for.
From there you stop being a passenger. You build reusable gems, wire up extensions, and learn exactly what to reach for and when. You prototype in Google AI Studio, make your first real calls to the Gemini API, and ground answers in Google Search so your outputs stand up to scrutiny.
Engineers on your team will respect this next part. You take the Gemini CLI into your terminal, run agentic coding, review pull requests, and go end to end from issue to merged pull request. You stand up agents with the agent development kit, orchestrate several of them, and set the guardrails on permissions, review, and cost that keep autonomy from becoming a liability.
Then you go deeper: function calling, structured outputs, embeddings, RAG on your own files, and Vertex AI to take Gemini to production. The capstone ties it together in one real workflow.
By the end you will not be asking what Gemini can do. You will be deciding what it does next inside your organization.
What you'll master
- Choose the right Gemini model for cost, speed, and quality on any given task
- Deploy Gemini across Workspace while enforcing governance and data controls
- Build reusable gems and connect extensions to your live business apps
- Call the Gemini API and ground responses with Google Search for trustworthy output
- Run agentic coding from the CLI, from issue to merged pull request
- Orchestrate multiple agents with the ADK behind permission, review, and cost guardrails
- Ship a production Gemini workflow using RAG, embeddings, and Vertex AI
Modules
Covers the Gemini model family, when to use each version, and how multimodality, long context, and personalization extend what it can do.
Shows how to use Gemini across Docs, Gmail, Sheets, Slides, Meet, and Drive, plus the governance controls that keep company data protected.
Shows how to build reusable custom assistants, connect Gemini to your apps, and choose the right tool for each task.
Walks through prototyping prompts, making your first API calls, and grounding responses with Google Search and live data.
Shows how to use Gemini for agentic coding across the terminal, IDE, and GitHub, from a single issue to a merged pull request.
Shows how to build, orchestrate, and safeguard AI agents that automate work across Google Workspace using the agent development kit.
Shows how to extend Gemini with function calling, structured outputs, embeddings, and retrieval, then deploy it to production on Vertex AI.
Shows how to use Gemini across Google tools, automate repetitive tasks, and build a complete end-to-end workflow.