Phase 1: Foundations (AI Thinking & Core Concepts)

🔑 Goal: Build a rock-solid mental model of AI so you understand what you’re doing, not just pressing buttons.

• Mindset & Thinking Patterns
  • Learn “AI-first thinking” → always asking “How can AI automate, optimize, or augment this?”
  • Study AI Generalist Framework → Learn to connect AI to business, coding, art, science.
• Core Concepts
  • What is AI? What it’s not.
  • Difference: AI vs ML vs DL vs AGI
  • Types of AI: Narrow AI, Generative AI, Predictive AI, Symbolic AI.
• Mathematical Intuition (not deep math, just enough intuition)
  • Probability, vectors, matrices, optimization.
  • Neural networks basics (neurons, layers, weights).

Deliverable:

A mental map of AI fields, with clarity on how they connect.

Phase 2: Essential AI Tools Mastery

🔑 Goal: Get hands-on with modern AI tools to create immediately useful outputs.

• Text AI (LLMs)
  • GPT-5, Claude, LLaMA, Mistral → learn prompting, context engineering.
  • Skills: Prompt Engineering, Chain-of-Thought Design, Multi-agent orchestration.
• Image AI
  • MidJourney, Stable Diffusion, Leonardo AI.
  • Skills: Photorealism prompts, style transfer, concept art creation.
• Audio AI
  • ElevenLabs, OpenVoice, RVC.
  • Skills: voice cloning, AI narration, podcast automation.
• Video AI
  • Runway, Pika, Kaiber.
  • Skills: text-to-video, video editing automation.
• Code AI
  • GitHub Copilot, Cursor, Code Interpreter.
  • Skills: AI pair programming, API integration, debugging automation.

Deliverable:

A portfolio of text, images, audio, and video made entirely with AI tools.

Phase 3: AI Coding & Automation (The Power Stage)

🔑 Goal: Learn to control AI with code and automate tasks, not just prompt.