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AI Engineer

50 chapters
·Introduction
01 Fundamentals & Models5
  • 01
    LLM API Basics
    30 min
  • 02
    AI Model Comparison
    20 min
  • 03
    ML & Deep Learning Fundamentals
    30 min
  • 04
    Transformers & Attention Basics
    30 min
  • 05
    Prompt Engineering
    45 min
02 Context & RAG6
  • 06
    Context Fundamentals
    30 min
  • 07
    RAG Systems Introduction
    60 min
  • 08
    🔒LangChain Framework
    60 min
  • 09
    Context Engineering & Memory
    35 min
  • 10
    Context Compression & Optimization
    35 min
  • 11
    Context Degradation Patterns
    30 min
03 Tools & Capabilities5
  • 12
    Function Calling & Tool Use
    35 min
  • 13
    Tool Design Principles
    35 min
  • 14
    Multimodal & Tool Chains
    40 min
  • 47
    Advanced Tool Use with the Claude API
    40 min
  • 48
    MCP Code Execution: Calling Tools Like a Code Library
    25 min
04 Agentic Workflows8
  • 15
    🔒AI Agent Development Basics
    90 min
  • 16
    System Prompt Design in Practice
    45 min
  • 17
    System Prompt Case Studies
    30 min
  • 18
    Agent Framework Overview
    40 min
  • 19
    Agent Framework Comparison
    45 min
  • 20
    Multi-Agent Patterns
    35 min
  • 21
    Advanced Agent Topics
    45 min
  • 49
    Harness Design Patterns for Long-Running Agents
    25 min
05 Evals & LLM Ops5
  • 22
    Evaluation & Quality Monitoring
    45 min
  • 23
    LLM-as-a-Judge Evaluation
    35 min
  • 24
    Synthetic Data & Augmentation
    30 min
  • 25
    LLM Platform & Gateway
    35 min
  • 26
    Workflow & Automation
    40 min
06 Safety & Deployment6
  • 27
    Security & Threat Modeling
    35 min
  • 28
    Data Governance & Privacy
    30 min
  • 29
    Deployment & Cost Optimization
    35 min
  • 30
    🔒Production Deployment
    90 min
  • 31
    Debugging & Incident Playbook
    35 min
  • 50
    Claude Code Sandboxing: Dual-Layer Isolation
    25 min
07 AI Coding & Advanced Practice13
  • 32
    AI Coding Workflow
    40 min
  • 33
    Vibe Coding in Practice
    45 min
  • 34
    AI Rules Configuration
    30 min
  • 35
    🔒MCP Development Best Practices
    45 min
  • 36
    🔒MCP Publishing Guide
    25 min
  • 37
    The Skills Paradigm: From Agents to Skill Libraries
    35 min
  • 38
    Claude Code Internals: Context & Memory Management
    45 min
  • 39
    Claude Code Examples
    30 min
  • 40
    AI Product & UX
    35 min
  • 41
    🔒Continuous AI Rules Improvement
    30 min
  • 42
    PR Review Methodology
    20 min
  • 43
    Code Analysis Options
    15 min
  • 44
    GitHub Issue Analysis
    15 min
08 Model Layer: Fine-Tuning & Open Models2
  • 45
    Fine-Tuning with LoRA / QLoRA / PEFT
    35 min
  • 46
    Open-Weight Models, Local Deployment & Routing
    30 min
Resources
  • 🗺️ Learning Roadmap
  • 📚 Wiki Docs
  • 📋 Cheat Sheets
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