Prompt Engineering: The Complete Guide

Can you survive as a developer in the rapidly developing AI era? 🧐

Today, the development trend is rapidly developing beyond simple web development to AI technology . Are you prepared? In order to not fall behind in the next era in this changing environment, you need to think about what capabilities are truly important in AI development. ' Prompt design ability ' is the foundation.

Prompt design can be left to prompt engineers? Prompt design skills are no longer a specialized skill for a certain profession . In the past, when information retrieval technology first appeared, the difficult search technology gave rise to the profession of 'information retrieval specialist'. Does that profession exist now? No.

In the future, developers will have to design prompts as if they were writing code . Now, prompt design has become a basic language-level skill that everyone should learn, just like learning Java . Through this lecture, you will systematically learn what LLM is, from basic concepts to advanced prompt design techniques . By first learning the essential skills of the AI era, you will be able to grow into a developer who is one step ahead. I believe this lecture will be a solid foundation for your career jump.”

Why I Created This Course

• Since the birth of the web, countless developers have jumped into web development, and this has created a new technology ecosystem. Now, with the advent of large-scale language models (LLMs) , another paradigm shift is beginning. In the future AI era, application development will become as natural as 'web development', and the core competency leading this is the ability to design prompts.

• I also learned this while making AI applications. It is not enough to simply ask questions to the model and receive results, but it is necessary to have the 'basics' to derive the desired answers . These basics are the skills that future developers must have . Just like learning languages such as Java or Python, the ability to design prompts is now also an essential skill.

• In this flow, I planned this lecture as a preparation for the coming era. I have spent a lot of time on this lecture for the past four months. I sat in front of my laptop on weekdays and weekends, overturning drafts, reviewing papers, thinking about better delivery methods, creating practical examples, and refining concepts. This lecture, which was born that way, contains all the things I personally felt and realized, as well as the core things that I want future developers to know. I hope this lecture will be a solid foundation for developers entering the AI era.

  
  

Lecture Features

📌 It is structured so that you can gradually learn everything from the basic concepts of what LLM is to advanced prompting techniques , and expand your skills step by step based on a solid foundation.

📌 We provide practical know-how that can be applied immediately in an actual service environment through Anthropic API integration and model parameter setting methods .

📌 By learning prompt design methods and evaluation techniques , you can gain the ability to accurately elicit desired responses, thereby maximizing the efficiency of model utilization.

📌 You can learn strategies to solve complex problems step by step and maximize the potential of the model through advanced techniques such as In-Context Learning, Decomposition, Self Criticism, and Ensembling .

📌 Flow Engineering and Auto Prompt Engineering help you build workflows that optimize the design, management, and automation of prompts to maximize development productivity and maintain consistent quality.

📌 Through advanced prompting techniques analyzed and applied in approximately 60 recent papers , this course presents practical strategies based on cutting-edge research results.

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After class

• Beyond simply calling the LLM, you will gain the ability to design sophisticated prompts to elicit the exact answers you want.

• With an understanding of the different LLM models, you can choose the optimal prompting strategy for your situation and goals.

• By learning automated prompt design and conversation flow management techniques, you will be able to achieve efficient and consistent results even in complex service environments.

• Advanced techniques such as In-Context Learning, Self Criticism, and Ensembling can overcome model limitations and elevate service quality to the next level.

• By acquiring 'prompt design skills' for the AI era, you will secure a solid foundation to grow into a competitive developer in the market.

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Things to note before taking the class