Essential AI Agent Fundamentals for Immediate Workplace Use – From Core Concepts You Can Apply Right Now to Practical Knowledge!

Q1. Um... I've done a little coding, but LLM and RAG are quite unfamiliar to me. I'm not a complete beginner, but could a novice also take this course? 🥹

Yes! Absolutely! Actually, think of this course as a 'cheat key' designed specifically for people like you! 🚀 Since LLMs are so hot these days, you probably thought "I should try this too!" and called the API a few times, but when you tried to input your company's data, you got hallucinations and felt frustrated, right? This course will solve that vague uncertainty. Rather than complex theories, we'll focus on "So how exactly should I use this?" and help you understand all the core principles of LLM and RAG within 90 minutes. As long as you have basic coding skills, you'll be fine! 💪

Q3. Our team is also discussing LLM adoption, but we keep fighting with the development team over "fine-tuning vs RAG"... 😂 If I take this course, can I end this tiresome debate?

A3. 😆😆😆😆😆 No more tedious debates - we can finally put an end to them! 😇 By taking this course, you'll be able to establish clear criteria for when to use fine-tuning and when to use RAG. You'll get answers to the questions that PMs and planners are most curious about, such as "How much will it cost?", "What about data security?", and "How will we reflect the latest information?" Instead of frustrating tug-of-war with the development team, you'll be able to make efficient decisions based on clear evidence. I'll help you arm yourself with the logic to convince your team! 🤝

Practice Environment

• Operating System and Version (OS): Windows 10 or higher, macOS 12 or higher, Ubuntu 22.04 LTS or higher

• Tools Used: Python

• Development Environment: IDEs such as Visual Studio Code, PyCharm, etc. can be used

• PC Specifications: CPU i5 or higher, Memory 16GB or higher, Disk 512GB, Integrated graphics card, etc.

Learning Materials

• Learning materials format provided (PDF, GitHub links, etc.)

• Features and precautions regarding volume, capacity, and other learning materials, etc.

Prerequisites and Important Notes

• It would be great if you have some simple Python coding experience

  
  

• Questions/answers and future updates will be conducted as needed.

• All copyrights for lecture-related content, including lectures and learning materials, belong to the author.

• Without prior written consent from the copyright holder, any unauthorized reproduction, distribution, transmission, creation of derivative works, and commercial use of this material is strictly prohibited.