Coding with AI
- Código del Curso CAI
- Duración 1 Día
Otros Métodos de Impartición
Método de Impartición
Este curso está disponible en los siguientes formatos:
-
Clase de calendario
Aprendizaje tradicional en el aula
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Aprendizaje Virtual
Aprendizaje virtual
Solicitar este curso en un formato de entrega diferente.
Temario
Parte superiorCoding with AI Course Overview
There’s no doubt that AI can make developers more efficient and productive. It’s also a great learning aid, enabling individuals to acquire knowledge in their own way and at their own pace. But it has its drawbacks too. It’s costly. LLM responses may be of poor quality, wrong, or even malicious. Developers must know enough to critique the code produced, and they must be disciplined enough to avoid cognitive atrophy.
This course deals with key AI concepts including language models, prompting, context, and agents.
It provides comprehensive coverage of GitHub Copilot in VS Code specifically, though the concepts are applicable to other AI coding assistants too. Delegates will learn how to exploit suggestions, agents, context, tools, slash commands, and smart actions. Delegates will further learn how to customise Copilot and to use it safely and securely.
Exercises and examples are used throughout the course to give practical hands-on experience with the techniques covered.
Calendario
Parte superior-
- Método de Impartición: Aprendizaje Virtual
- Fecha: 09 noviembre, 2026 | 10:30 AM to 6:00 PM
- Sede: Aula Virtual (W. Europe )
- Idioma: Español
Dirigido a
Parte superiorWho will the Course Benefit?
The Coding with AI course is primarily aimed at developers, analysts, and engineers (those who write code), but it may also be of interest to non-technical people responsible for teams that produce code.
Objetivos del Curso
Parte superiorCourse Objectives
The course aims to provide the delegate with the skills and knowledge necessary to use AI tools, specifically GitHub Copilot in VS Code, to become more efficient and productive. It also seeks to provide the delegate with an understanding of the way in which LLMs and agents work, and the risks and safeguards involved.
Contenido
Parte superiorCourse Contents
Course Introduction
- Administration and course materials
- Course structure and agenda
- Delegate and trainer introductions
Session 1: LANGUAGE MODELS AND AGENTS
- Models
- Prompts
- Prompt engineering
- LLM characteristics
- Thinking and reasoning
- Which model?
- Context
- Context window
- Tools
- What is an agent?
- The agent loop
- Agent types
- Subagents
- Memory
Session 2: GITHUB COPILOT IN VISUAL STUDIO CODE
- About GitHub Copilot
- Setup
- Suggestions
- Agents (chat)
- Prompting
- Context
- Tools
- Reviewing
- Editing previous chat requests
- Checkpoints
- Chat participants
- Inline chat
- Generate code context menu
- Slash commands
- Smart actions
- Switching accounts
- Signing out
- Disabling AI features
Session 3: COPILOT CUSTOMISATION
- Reusable prompts
- Custom instructions
- Custom agents
- Model Context Protocol (MCP)
Session 4: COPILOT SECURITY
- Execution and access
- Supply chain dependencies
- Approval automation
- Information exposure
- Prompt injection
- Trust boundaries
- Controlled scope
- Transparency
- Secrets management
- Recommended security baseline
- Enterprise policies
Pre-requisitos
Parte superiorRequirements
Delegates attending this course will, ideally, be able to write code independently. This does not apply to those attending with a view to understanding the concepts, risks, and safeguards only.
