ChatGPT 4.0 Complete Use Secrets: How LLMs Boost Work & Explore New Frontiers

I. INTRODUCTION

AI technology is changing our life and work at an astonishing speed. This course will take you to comprehensively master GPT 4.0 large-language-model usage tricks, helping you work twice as effectively with half the effort and explore unknown fields.

II. Course Content:

1. This Course's Learning Content:
Understand this course's learning content and objectives, laying the foundation for learning.

2. Methods Needed to Practice This Course's Content
Learn the methods and tricks needed to practice this course's content, lifting learning efficiency.

3. ChatGPT and GPT-4's Evolution History:
Understand ChatGPT and GPT-4's development history, mastering their evolutionary trajectory.

4. Feeding GPT-4 'Prompts' So It 'Works' for You:
Learn how to give GPT-4 prompts to get satisfying answers.

5. How to More Efficiently Create 'Prompts':
Master methods of creating efficient prompts, lifting GPT-4 application efficiency.

6. How to Make GPT-4 Give You More Satisfying Answers:
Learn how to guide GPT-4 to get more satisfying answers.

7. Great Open-Source 'Prompt' Libraries:
Introduce excellent open-source prompt libraries for learners' use.

8–18. Different Types of Prompts:
Learn fill-in-the-blank, comparison, reverse, question-then-answer, table, chain-of-thought, summary, reasoning, translation, expansion, and other prompt types, lifting GPT-4 application flexibility.

19–26. GPT-4 Application Examples:
Learn practical tricks of using GPT-4 to lift writing, analyze data, write speeches and make PPTs, write product creative copy, write ad copy, write official-account articles, create original songs, write time-travel novels, design questionnaires, etc.

27–30. Using GPT-4 to Write Code:
Learn using GPT-4 to write, explain, and debug code, lifting programming efficiency.

31–32. Python Connecting to Baidu Qianfan LLM Platform Practice:
Hands-on practice—learn using Python to connect to Baidu Qianfan LLM Platform, developing chatbots and AI customer-service assistants.

33–37. Machine-Learning Models:
Learn machine learning's linear-regression, SVR-regression, decision-tree-regression, K-Means, and XGBoost model application tricks.

That's this course's content; we hope through learning you'll fully master GPT-4.0 usage tricks, lift work efficiency, and explore unknown-field possibilities.

III. Course Catalogue: