AI‑Assisted Coding Training

Learn via : Virtual Classroom / Online
Duration : 2 Days
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Description

The purpose of this training is to clearly understand LLM fundamentals (token, prompt, embedding/vector), develop a hands-on example using a basic RAG approach, and teach tool/service integration via the Model Context Protocol (MCP). The training aims to provide a production-oriented mindset with enterprise-scale best practices such as security, versioning, testing, and observability.

Learning Outcomes

  • Understand token, prompt, and embedding/vector concepts
  • Integrate local or enterprise services with LLMs via MCP and build a design-to-code prototype using FigmaMCP
  • Apply security, versioning, testing, and observability best practices in production-focused workflows

 

Audience

  • Backend, Frontend, and Mobile Developers
  • Product and Prototyping Teams
  • Teams adopting LLM-assisted development within IDEs

Outline

LLM Fundamentals & Hands-on Coding

  • Core concepts: LLMs, tokens, embeddings/vectors
  • Context window and token budget management
  • Prompt design (roles, formats, examples) and evaluation
  • Basic RAG: indexing, similarity search, retrieval flow
  • Code generation and refactoring
  • Test generation (unit/fixtures) and validation
  • Security and content filtering (PII masking)
  • Cost and performance optimization

Prompts, IDE Integrations & Best Practices

  • Advanced prompt patterns and anti-patterns
  • IDE integrations (VS Code, Cursor, Windsurf)
  • Rule sets and style guides
  • Practical workflows for code and test generation
  • Performance and cost optimization
  • Collaboration and review workflows
  • Project: Git-integrated design-to-code application

Prerequisites

Basic programming knowledge is required.