COURSE OUTLINE & HIGH-LEVEL LESSONS
The course is modular. Learners move through stages sequentially or start from their diagnostic result.
🔖Stage 1: AI & Prompt Engineering Essentials
Lesson 1: Introduction to AI & Large Language Models
Chapter 1: The AI Revolution Opening Digital Doors
- 1.1 From Gatekeeping to Democratization
- 1.2 The Evolving Landscape of AI Tools
- 1.3 Building Your AI Mental Model
- 1.4 Finding Your Inspiration Point
Chapter 2: Getting Started with Chat Interfaces
- 2.1 Navigating ChatGPT and Claude
- 2.2 Asking Effective Questions
- 2.3 Understanding Response Limitations
- 2.4 Your First AI Conversations
Chapter 3: Three Ways to Enhance LLM Responses
- 3.1 Clarity in Inputs
- 3.2 Iterative Refinement
- 3.3 Contextual Enrichment
- 3.4 Practical Response Enhancement Examples
Chapter 4: Understanding Context and Its Power
- 4.1 What is Context in AI Systems
- 4.2 Context Window Limitations
- 4.3 Strategic Context Management
- 4.4 From Simple Chats to Complex Interactions
Lesson 2: Mastering Prompt Engineering
Chapter 1: Prompt Engineering Frameworks
- 1.1 Chain of Thought Prompting
- 1.2 Zero-Shot Approaches
- 1.3 Few-Shot Learning with Examples
- 1.4 Comparing Framework Effectiveness
Chapter 2: System vs User Prompts Setting the Stage
- 2.1 Defining AI Behavior with System Prompts
- 2.2 Creating Effective User Queries
- 2.3 The Interplay Between System and User Inputs
- 2.4 Philosophical Implications of AI Guidance
Chapter 3: Advanced Techniques XML Delimiting and Structured Outputs
- 3.1 Controlling Output with XML Tags
- 3.2 Creating Multi-Section Responses
- 3.3 Anthropic's Prompting Guide Highlights
- 3.4 Ensuring Consistency with Structured Formats
Chapter 4: Prompt Tuning vs Custom Assistant Building
- 4.1 When to Use Simple Prompt Tuning
- 4.2 Limitations of Static Prompts
- 4.3 Introduction to Custom Assistants
- 4.4 Decision Framework for Approach Selection
Activity: Reusable Meeting Summarizer Prompt
- Meeting Transcripts
- Placeholder Template.md
- Activity Instructions.md
- Example Solutions.md
Lesson 3: AI as Gateway to Unrestricted Learning
Chapter 1: Breaking Down Knowledge Barriers
- 1.1 Traditional Learning Gatekeepers
- 1.2 AI as Universal Translator of Knowledge
- 1.3 From Information to Understanding
- 1.4 Case Studies Barrier Removal
Chapter 2: Adaptive Learning in the AI Era
- 2.1 Self-Paced Exploration
- 2.2 Navigating Learning Depth vs Breadth
- 2.3 Interest-Driven Tangents
- 2.4 Creating Personalized Learning Paths
Chapter 3: Bridging Concept to Application
- 3.1 The Knowledge-Application Gap
- 3.2 AI-Assisted Project-Based Learning
- 3.3 From "I Know" to "I Can Do"
- 3.4 Practical Application Frameworks
Chapter 4: Accessing Previously Gatekept Fields
- 4.1 Breaking Into Technical Domains
- 4.2 Creative Fields Without Formal Training
- 4.3 Professional Skills Development
- 4.4 Ethical Considerations of Access
Activity: Personal AI Learning Plan
- Learning Plan Template.md
- Self-Assessment Worksheet.md
- AI Prompt Library for Learning.md
- Example Learning Plans.md
Lesson 4: Connecting AI to the World
Chapter 1: Extending AI Capabilities with External Knowledge
- 1.1 Limitations of Base LLM Knowledge
- 1.2 Knowledge Base Creation and Curation
- 1.3 Retrieval Augmented Generation Concepts
- 1.4 Specialized Domain Knowledge Integration
Chapter 2: Tools and Actions Empowering AI to Do More
- 2.1 Understanding AI Tool Use
- 2.2 Common Tool Categories and Functions
- 2.3 Function Calling and API Integration
- 2.4 Multi-Tool Orchestration
Chapter 3: Crafting System Prompts for Enhanced Capabilities
- 3.1 System Prompts for Tool Use
- 3.2 Knowledge Base Integration Patterns
- 3.3 Error Handling and Fallback Strategies
- 3.4 Balancing Flexibility and Constraints
Chapter 4: Building Integrated AI Solutions
- 4.1 From Components to Cohesive Systems
- 4.2 Designing for User Experience
- 4.3 Testing and Iterating AI Systems
- 4.4 Scaling and Maintenance Considerations
Final Activity: Custom HuggingChat Assistant
- Tool Selection Guide.md
- Knowledge Base Creation Template.md
- System Prompt Builder.md
- Testing Scenarios.md
- Example Assistants.md
Total Stage 1 Content:
- • 4 comprehensive lessons
- • 16 in-depth chapters
- • 64+ detailed sub-topics
- • 3 hands-on activities with templates and examples
🔖Stage 2: Accelerated Core Programming Fundamentals
- Lesson 1: Programming Fundamentals via AI (Python, JS)
- Lesson 2: Understanding Variables, Loops, and Functions with AI Examples
- Lesson 3: Essential Data Structures & Algorithms (Arrays, Lists, Sorting)
- Lesson 4: Object-Oriented Programming Simplified with AI
- Practical Project: AI-Enhanced Mini Application (Text-based game or calculator)
🔖Stage 3: AI-Assisted IDE & Developer Workflow Mastery
- Lesson 1: Mastering Your IDE (VS Code, JetBrains, Cursor)
- Lesson 2: Integrating and Leveraging GitHub Copilot for Rapid Development
- Lesson 3: Debugging and Refactoring Efficiently with AI
- Lesson 4: Version Control Simplified (Git/GitHub with AI assistance)
- Practical Project: Create and Debug a Simple AI-generated Web App
🔖Stage 4: AI-Enhanced Framework & Library Expertise
- Lesson 1: Rapid Frontend Development with React/Next.js + AI
- Lesson 2: Backend Mastery with Node.js/Express or FastAPI with AI
- Lesson 3: Databases Made Easy (PostgreSQL & SQL via AI)
- Lesson 4: Integrating Frontend & Backend Seamlessly
- Practical Project: AI-powered Web Platform MVP
🔖Stage 5: Automation, Deployment, and DevOps Acceleration
- Lesson 1: Scripting & Automation Basics (Bash/Python via AI)
- Lesson 2: Containerization Simplified (Docker with AI)
- Lesson 3: Introduction to CI/CD (AI-assisted deployments)
- Lesson 4: Cloud Deployment Basics (AWS, Vercel, Railway via AI)
- Practical Project: Fully Automated Deployment of AI-assisted App
🔖Stage 6: AI-Driven Software Architecture & System Design
- Lesson 1: Understanding APIs and System Architecture via AI
- Lesson 2: Scalable Architectures & Microservices Explained
- Lesson 3: Databases, Caching, and System Optimization with AI
- Lesson 4: AI-enhanced Architectural Diagramming
- Practical Project: Design and Document a Complex Application System (AI-generated)
🔖Stage 7: Specialized AI Integration & Application Development
- Lesson 1: API Integrations (OpenAI, Hugging Face, LangChain)
- Lesson 2: Building Retrieval-Augmented Generation (RAG) Systems
- Lesson 3: Developing AI Agents & Autonomous Workflows
- Lesson 4: Customizing AI Models & Fine-tuning Basics
- Practical Project: AI-powered SaaS Prototype or AI Agent App
🔖Stage 8: Continuous Learning & Elite-level Developer Mindset
- Lesson 1: Staying Cutting-edge (AI-curated daily summaries & alerts)
- Lesson 2: Strategic Networking & AI-assisted Learning Communities
- Lesson 3: Daily AI-powered Practice and Skill Expansion Strategies
- Lesson 4: Long-term Career Development with AI Tools
- Practical Project: Personalized AI-assisted Roadmap for Ongoing Development