Tool or Technology
TT0166

Gemini Code Assist Foundations

Code, Debug & Review Smarter with AI

Gemini Code Assist
Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Build foundational proficiency in using Gemini Code Assist for AI-assisted software development inside supported IDEs.
  • Use code completion, generation, chat, and transformation capabilities to accelerate common development activities.
  • Apply Gemini Code Assist to understand existing codebases, debug problems, generate tests, refactor code, and improve documentation.
  • Use Agent Mode for structured multi-step development tasks while maintaining developer review and approval.
  • Apply secure, responsible, and verification-driven practices when using AI-generated code in organisational development environments.

Technology covered

Gemini Code Assist Standard / EnterpriseIDE ChatCode CompletionsCode GenerationSmart ActionsCode TransformationsAgent ModeModel Context Protocol (MCP)GitHub Code Review

Who should attend

  • Software Developers
  • Frontend Developers
  • Backend Developers
  • Full-Stack Developers
  • Application Developers
  • Software Engineers
  • QA & Test Automation Engineers
  • Cloud Developers
  • DevOps Engineers
  • Technical Leads
  • Engineering Productivity Teams

Prerequisites & Participant Readiness

  • Basic programming knowledge in at least one programming language
  • Familiarity with functions, classes, files, dependencies, and common development concepts
  • Basic experience using VS Code, JetBrains IDEs, Android Studio, or another supported development environment
  • Basic understanding of source-code repositories is helpful
  • Familiarity with Git is beneficial
  • No previous Gemini Code Assist experience required

TOC Modules

Concepts
  • Understanding Generative AI in the software-development lifecycle
  • Understanding Gemini Code Assist Standard and Enterprise editions
  • Understanding IDE-integrated AI development assistance
  • Understanding code completions, generation, transformations, chat, and agentic workflows
  • Understanding strengths, limitations, and developer accountability for AI-generated code
Practical activities
  • Exploring Gemini Code Assist inside a supported IDE
  • Asking Gemini to explain a simple code component
  • Completing a guided development activity using Gemini Code Assist
  • Reviewing generated code before accepting changes

Scenarios

Development Requirement to Tested Feature

Requirement → Codebase Context → Gemini Chat / Agent Plan → Code Generation → Refactoring → Automated Tests → Developer Review

Participants use Gemini Code Assist to understand an existing application, identify affected components, implement a small feature, generate suitable tests, and validate the resulting changes before integration.

Pull Request to AI-Assisted Code Review

Developer Changes → GitHub Pull Request → Gemini Summary → Automated Code Review → Issue Investigation → Approved Fix → Human Approval

Participants use Gemini Code Assist to analyse a pull request, identify potentially significant issues, evaluate suggested corrections, and prepare verified code for final human review.

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