Tool or Technology
TT0082

JetBrains AI Assistant Foundations

Code, Understand & Develop Smarter with AI

JetBrains AI Assistant
Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Build foundational proficiency in using JetBrains AI Assistant within modern software-development workflows.
  • Apply effective prompting and project context to generate, understand, modify, and improve source code.
  • Use AI-assisted capabilities for code completion, explanation, debugging, refactoring, documentation, and test generation.
  • Improve development and version-control productivity using AI-generated reviews, summaries, and commit information.
  • Apply appropriate code validation, security, privacy, and developer-review practices when working with AI-generated code.

Technology covered

JetBrains AI AssistantAI ChatAI Code CompletionAI ActionsPrompt LibraryCoding AgentsAI DiffVersion Control Integration

Who should attend

  • Software Developers
  • Java & JVM Developers
  • Python Developers
  • Frontend & Web Developers
  • Backend Developers
  • Full-Stack Developers
  • QA & Test Automation Engineers
  • Software Engineers
  • Technical Leads
  • Junior & Associate Developers

Prerequisites & Participant Readiness

  • Basic programming knowledge in at least one programming language
  • Familiarity with functions, classes, variables, files, and basic development concepts
  • Basic experience using a JetBrains IDE such as IntelliJ IDEA, PyCharm, WebStorm, Rider, GoLand, or similar
  • Basic familiarity with Git and source-code repositories is helpful
  • No previous JetBrains AI Assistant experience required
  • Availability of specific AI capabilities may depend on the IDE, organisation settings, AI configuration, and enabled models

TOC Modules

Concepts
  • Understanding Generative AI in the software-development lifecycle
  • Understanding JetBrains AI Assistant and its integration within JetBrains IDEs
  • Exploring AI Chat, code completion, AI Actions, and coding-agent capabilities
  • Understanding how IDE and project context influence AI-generated responses
  • Understanding the developer's responsibility for reviewing AI-generated code
Practical activities
  • Activating and exploring AI Assistant in a supported JetBrains IDE
  • Using AI Assistant to complete a simple development task

Scenarios

Requirement to Tested Implementation

Development Requirement → AI Chat → Project Context → Code Generation → Refactoring → Unit Tests → Developer Review

Participants use JetBrains AI Assistant to understand a requirement, generate and refine implementation code, create relevant tests, and validate the result before integration.

Existing Code to Maintainable Solution

Existing Code → AI Explanation → Problem Identification → Refactoring → Documentation → Change Summary

Participants use AI Assistant to understand unfamiliar or difficult-to-maintain code, identify improvements, refactor the implementation, and create supporting technical documentation more efficiently.

Related programmes

Continue with programmes from the same capability area.

Take the next step

Ready to make this programme work for your team?

Customise modules, duration and business scenarios for your team.

Instructor-ledVirtualHybrid

Designed around your roles, tools and real workflows.