Gemini for Developers: Mastery — API & AI Studio

Build current Gemini API integrations from AI Studio prototypes with multimodal inputs, structured outputs, function calling and code-enforced safety, retrieval and operating controls

What this course covers

The course runs across 10 topics, each one a short adaptive session rather than a recorded lecture. The tutor explains the idea, works an example, checks understanding, and adjusts the next step to the answer given.

Google AI Studio: prototype to Gemini API — Separate AI Studio browser prototyping from Gemini API production work. Use current Google Gen AI SDK documented request/response shapes; fake calls suffice for required final.
Multimodal inputs and data boundaries — Scope text/image/document inputs, permissions and retention; validate supported types and minimize tenant data.
Structured outputs and application validation — Request supported schema-constrained output and separately validate business/authorization rules. Handle incomplete/safety-blocked output.
Function calling: model content and tool responses — Read functionCall parts, preserve model content and append functionResponse parts with name and response object. Never copy OpenAI/xAI tool schemas into Gemini.
Application-owned tool guardrails — Allowlist tools; validate arguments and enforce amount, approval and tenant rules before side effects. Bound turns/time and handle missing candidates.
Grounding and retrieval — Use available grounded search or application retrieval with source attribution and tenant filters; never assume citations prove correctness.
Safety and prompt-injection resistance — Handle safety outcomes and reject instructions inside retrieved content; source text cannot grant tool authority.
Context caching and cost controls — Use caching only where supported, track tokens/calls and budgets, and select models by measured requirements without fixed version names.
Rate limits and resilient retries — Bound backoff/jitter for transient failures and protect side effects with idempotency and audit metadata excluding secrets.
Evals and production handoff — Run deterministic tool-loop tests plus grounded/missing-source evaluations; document permissions, monitoring and rollback. Do not teach unavailable tuning as generally supported.

Skills you build

Results are measured against named skills in the OneRange taxonomy of more than 10,000 skills, so a manager sees proficiency per skill rather than a completion tick.

Who it is for

Software developers and technical builders. The material is pitched at expert level, and takes roughly 180 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.

It sits in the Tool: Gemini track of the Vero AI Catalog, and can be assigned to one person, a team, or the whole company.

How it is delivered and assessed

Delivery is conversational and interactive. There is no video to sit through and no slide deck to click past.

Understanding is checked with a code assessment of 5 items, with a pass mark of 70%.

Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.

Also in this track

All Gemini training courses →
Gemini: Mastery — Leading Work with Gemini — Lead reliable work with Gemini through delegation, description, discernment and diligence. Package expertise, verify outputs, supervise available tools and measure impact without a technical background
Gemini for Developers: Advanced — Agentic Engineering — Coordinate current Google Antigravity engineering agents with task contracts, isolated changes, verified artifacts, least privilege and integration review
Gemini: Advanced — Power Workflows & Automation — This course fills the step between everyday fluency and building on the platform: running Gemini at an expert level without writing code. Learners design multi-step workflows, automate recurring work with skills, Workspace automations, and Deep Research, and set personal systems that compound over weeks. They finish as the person on the team others come to for Gemini technique.
Gemini: Core — Google Workspace — This course goes deep on Gemini across Google Workspace. Learners use Gemini in Docs, Sheets, and Slides, in Gmail and Meet, and apply NotebookLM and Deep Research for grounded answers. The outcome is meaningfully faster, AI-assisted Workspace workflows.
What's New in Gemini for Everyone — A short refresher on the latest Gemini for Everyone updates
Gemini for Developers Pathway — Gemini for developers from coding in Gemini chat to the Antigravity CLI and Google Antigravity, agentic engineering, and guarded production integrations on the Gemini API and AI Studio. Also includes 4 optional playbooks (Testing, Code Review, Refactoring & Migration, Docs & Onboarding) to take any time after Essentials; they don't count toward the certificate.

Frequently asked questions

How long does this course take?

It runs roughly 180 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.

How is it assigned to a team?

An administrator assigns it from the Vero dashboard to one person, a team, a department or the whole company, and sees progress and results per person and per skill.

Can we customise it with our own documents and terminology?

Yes. Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.

Course code TUL-GEM-DEV-301.