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Mastering GPT in Your Daily Work
Course Introduction
Course Introduction (3:28)
MODULE 1: LLM / GPT Intro & Capabilities
1.1 Basics of AI (6:14)
1.2. Introduction to Large Language Models (LLMs) (8:21)
1.3. How does ChatGPT work? (6:22)
1.4. GPT Performance History (3:39)
1.5. Context Window & Pricing of ChatGPT (2:25)
1.6. LLM Application Areas (18:35)
1.7. Limitations of ChatGPT (7:57)
1.8. OpenAI Playground (4:43)
1.9. Comparing GPT-4 with Bard (2:22)
1.10 Module 1 – Exercise (0:52)
MODULE 2: Prompt Engineering ("Prompting")
2.1. General Prompting Tips & Techniques (5:48)
2.2. Chain of Thought (CoT) (1:31)
2.3. Self-reflection (4:05)
2.4. In-context Learning + Few-shot Prompting (2:32)
2.5. Input-Output Prompting (2:33)
2.6. Role Prompting (2:33)
2.7. Prompt Chaining (2:48)
2.8. CO-STAR (3:57)
2.9. ChatGPT Custom Instructions (3:04)
2.10. Module 2 – Exercises (1:54)
MODULE 3: GPT Tooling
3.1. Extensions for ChatGPT (8:49)
3.2. GPT Plugins (7:15)
3.3. (Custom) GPTs (19:18)
3.4. AI Image Generation Tool Overview (2:46)
3.5. Midjourney Live Example (5:55)
3.6. DALL·E 3 Examples (7:56)
3.7. Text-to-Video Tools & "AI Humans" (3:44)
3.8. Obsidian (3:24)
3.9. Agents & AutoGPT (5:39)
3.10. Module 3 – Exercises (3:25)
MODULE 4: Additional Topics & Outlook
4.1. LLMs and SEO (4:29)
4.2. Coding with LLMs (2:23)
4.3. LLMs and Data Protection / Copyright (9:53)
4.4. AI Safety & Ethics (15:06)
4.5. LLM Outlook (7:19)
4.6. Old vs. New "Turing Test" (3:47)
4.7. Artificial General Intelligence (AGI) (5:35)
4.8. Artificial Super Intelligence (ASI) (3:46)
4.9. Speculative AGI / ASI Timeline (5:29)
4.10. LLM Use Case Ideation Framework (2:49)
Course Outro
Course Outro (0:40)
2.4. In-context Learning + Few-shot Prompting
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