Tool or Technology
TT0168

Mastering Gemini Code Assist

Advanced AI Coding, Agentic Development & Enterprise Engineering

Gemini Code Assist
Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced expertise in applying Gemini Code Assist throughout the software-development lifecycle for coding, codebase understanding, refactoring, debugging, testing, documentation, review, and application modernisation.
  • Use Agent Mode to plan and execute complex multi-step engineering tasks involving files, terminal commands, repository context, built-in tools, and MCP integrations.
  • Apply Gemini CLI and IDE-based workflows to accelerate local and cloud-oriented engineering while maintaining appropriate developer review and execution controls.
  • Configure Gemini Code Assist Enterprise with private repository context and organisation-specific coding practices using Code Customization and governed GitHub code-review configurations.
  • Establish enterprise security, privacy, IAM, networking, governance, monitoring, and responsible-AI practices for production adoption of AI-assisted engineering.

Technology covered

Gemini Code Assist StandardGemini Code Assist EnterpriseGemini Code Assist ChatCode CompletionCode GenerationSmart ActionsAgent ModeGemini CLIGemini 3.5 FlashGemini 3.1 Pro where enabledModel Context Protocol (MCP)Code CustomizationGitHub Code ReviewDeveloper ConnectVS CodeJetBrains IDEsAndroid StudioCloud WorkstationsFirebaseCloud RunBigQueryDatabase StudioApigeeApplication Integration & Google Cloud

Who should attend

  • Software Developers & Application Engineers
  • Full-Stack Developers
  • Frontend & Backend Developers
  • Java, Python, JavaScript, TypeScript, Go & .NET Developers
  • Android Developers
  • Cloud Application Developers
  • Software Architects
  • Solution Architects
  • Technical Leads & Engineering Leads
  • DevOps & Platform Engineers
  • Site Reliability Engineers
  • QA & Test Automation Engineers
  • Application Modernisation Teams
  • Developer Productivity Teams
  • Enterprise Engineering & AI Teams

Prerequisites & Participant Readiness

  • Working knowledge of at least one programming language
  • Familiarity with Git, repositories, branches, commits, and pull requests
  • Understanding of software-development, debugging, testing, and code-review practices
  • Basic experience with VS Code, JetBrains IDEs, Android Studio, or another development environment
  • Basic command-line knowledge is recommended for Gemini CLI activities
  • Familiarity with APIs, JSON, and software integration concepts is beneficial
  • Basic understanding of Google Cloud is useful for cloud-oriented modules
  • No previous Gemini Code Assist course attendance is required
  • Hands-on enterprise features require a Gemini Code Assist Standard or Enterprise licence
  • Code Customization requires Gemini Code Assist Enterprise
  • Agent Mode and selected advanced capabilities may be Preview features or depend on administrator configuration

TOC Modules

Concepts
  • Understanding Gemini Code Assist Standard and Enterprise editions
  • Understanding Gemini Code Assist within the modern Google developer-tool ecosystem
  • Understanding AI-assisted coding across IDE, terminal, GitHub, and Google Cloud workflows
  • Differentiating code completion, conversational assistance, and Agent-based engineering
  • Understanding strengths, limitations, hallucinations, and developer accountability
Practical activities
  • Exploring Gemini Code Assist in a supported development environment
  • Comparing manual, AI-assisted, and Agent-driven development approaches
  • Mapping Requirement → AI Assistance → Code → Test → Review → Delivery

Scenarios

Enterprise Requirement-to-Reviewed Application Feature

Business Requirement → Private Repository Context → Gemini Code Assist Agent Mode → Implementation Plan → Multi-File Development → MCP / Development Tools → Automated Tests → GitHub Pull Request → Gemini Code Review → Human Approval

Participants build an end-to-end enterprise development workflow where Gemini understands organisational code context, plans and implements a substantial feature, validates the solution, and supports a governed pull-request review before integration.

Legacy Application Modernisation on Google Cloud

Existing Codebase → Architecture Analysis → Gemini Code Assist → Refactoring / Library Migration → Google Cloud Integration → Automated Tests → Security Validation → GitHub Review → Deployment-Ready Application

Participants modernise an existing application using AI-assisted codebase analysis, refactoring, dependency migration, cloud integration, testing, and governed code review while maintaining human accountability for architecture and production readiness.

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