1. AI Introduction
1.1. Core Skills in 2030
1.1.1. Image
1.2. History of AI
1.2.1. Foundation of Maths
1.2.1.1. Image
1.2.1.1.1. 200BC, Chinese mathematicians invent Matrix Calculus
1.2.1.2. Image
1.2.1.2.1. 1700, Newton and Leibniz invent Differentation
1.2.2. AI: 1950's Turing Test
1.2.2.1. Image
1.2.3. Machine Learning: 1980's Neural Network
1.2.3.1. Image
1.2.4. Deep Learning: 2012 CNN architecture, AlexNet
1.2.4.1. Image
1.2.5. Generative AI: 2020s ChatGPT
1.2.5.1. 2017 Transformer, "Attention is all you need"
1.2.5.1.1. Image
1.2.5.2. 2018, ASLM successfully built EUV machine
1.2.5.2.1. Image
1.2.5.3. 2022-Mar, NVIDA anounced H100 GPU (1,979 TFLOPS)
1.2.5.4. 2022-Nov: chatGPT moment
1.2.5.4.1. Image
1.3. AI Evolution
1.3.1. Image
1.3.1.1. Perception AI
1.3.1.1.1. Image
1.3.1.2. Generative AI
1.3.1.2.1. Image
1.3.1.3. Agentic AI
1.3.1.3.1. Image
1.3.1.4. Physical AI
1.3.1.4.1. Image
1.4. AI Types
1.4.1. Image
1.4.1.1. Artifical Narrow Intelligence (ANI)
1.4.1.2. Artifical General Intelligence (AGI)
1.4.1.3. Artifical Super Intelligence (ASI)
1.5. AI Training
1.5.1. Image
1.5.1.1. Unsupervised Learning
1.5.1.2. Supervised Fine-tune
1.5.1.3. Reinforcement Learning
1.6. AI Solutions
1.6.1. Stand-alone (Use)
1.6.2. Integration
1.6.3. Customization (Build)
2. GenAI Models
2.1. Text-to-Text
2.1.1. Foundation Models (LLM)
2.1.1.1. GPT-4.5
2.1.1.2. Claude Sonet 3.7
2.1.1.3. Grok 3
2.1.1.4. Reasoning Models
2.1.1.4.1. GPT-3o
2.1.1.4.2. Deepseek R1
2.1.1.5. Multimodal Models
2.1.1.5.1. GPT-4o
2.2. Text-to-Image
2.2.1. Stable Diffusion
2.2.2. MidJourney
2.3. Text-to-Speech
2.3.1. ElevenLabs
2.4. Text-to-Video
2.4.1. Sora
2.5. Speech-to-Speech
2.5.1. GPT-4o Advance Voice Mode
3. Prompting
3.1. LLMs' Basic Tasks
3.1.1. Understanding
3.1.1.1. Classification
3.1.1.2. Summarization
3.1.1.2.1. Gen MOM
3.1.2. Content Generation
3.1.2.1. Gen VB code
3.1.2.2. Write and Send email
3.1.3. Transformation
3.1.3.1. Editing
3.1.3.2. Infererence
3.1.4. Retrieval / Extraction
3.1.4.1. Legal docs extraction
3.1.5. Reasoning
3.2. Direct Prompting
3.2.1. Zero-shot Prompt
3.2.1.1. CRE Framework
3.2.1.1.1. Image
3.2.1.2. Detailed Instruction
3.2.1.2.1. Image
3.2.1.3. Persona
3.2.1.3.1. Image
3.2.1.4. Delimiters
3.2.1.4.1. Image
3.2.1.5. Output format
3.2.1.5.1. Image
3.2.2. One-shot Prompt
3.2.2.1. Image
3.2.3. Few-shot Prompt
3.2.3.1. Image
3.3. Advance Prompting
3.3.1. Chain-of-Thought / Step-by-Step Instruction
3.3.1.1. Image
3.3.2. Iterations and Consistency
3.3.2.1. Image
3.3.3. Prompt Chaining
3.3.3.1. Image
3.3.4. Clarification Prompting
3.3.4.1. Image
3.3.5. Lazy Prompting / Singel-Turn vs Multi-Turn
3.3.5.1. Image
3.3.6. Ask chatGPT
3.4. Prompt Evaluation
3.4.1. Image
3.5. LLMs' Parameters
3.5.1. Image
3.6. Customize a chatbot
3.6.1. OpenAI
3.6.1.1. Image
3.6.2. Copilot
3.6.2.1. Image
3.7. Human-in-the-loop
3.7.1. Image
4. AI Limitations
4.1. Bias
4.1.1. Image
4.2. Drift
4.2.1. Knowledge Cutoff
4.2.1.1. Image
4.3. Halluciations
4.4. Privacy / Security
4.4.1. Self-host vs Cloud
4.4.2. Deepfake
4.4.3. Voice cloning
4.4.4. Prompt Injection
5. AI Next Stage
5.1. Agentic AI
5.1.1. Manus AI
5.1.2. LangGraph
5.1.3. CrewAI
5.2. Domain-Specific Models
5.2.1. Finance
5.2.1.1. FIN-GPT
5.2.1.2. BloombergGPT
5.2.2. Healthcare
5.2.2.1. Med-PALM2
5.2.2.2. ClinicalBERT
5.2.3. Legal
5.2.3.1. Paxton AI
5.3. Physical AI
5.3.1. Atlas
5.3.1.1. Link
5.3.2. Optimus
5.3.2.1. Link
5.3.3. Unitree
5.3.3.1. Link
5.4. Quantum Computing
5.4.1. Image