Technology Sharing

Welcome to our project practice course. This issue is about "Large Language Model Prompt Word (Prompto) Engineering Practice".A simple principle review + detailed project practice mode, providing code-level practical explanations for a specific topic.

In this course

Prompt Engineering is an important field in natural language processing (NLP) and machine learning. It focuses on how to design effective prompts to guide the model to generate high-quality text. Good prompts can help the model understand task requirements and improve the relevance and accuracy of generated text. In applications such as chatbots, text generation, and question-answering systems, prompt engineering is crucial to improving user experience and system performance.

This course will focus on the practical application of large language model prompt engineering, including the definition of prompt, why to write a good prompt, the basic methods and advanced techniques for writing a good prompt, and the comprehensive practice of prompt based on Zhipu Qingyan API - creating a dedicated air ticket booking assistant.The price is 69 yuan, and the explanation lasts about 100 minutes., with a Q&A group and code,The course content and duration of each part are as follows:

The course outline is as follows:

Let's take a quick look at the contents of each section:

Part 1: What is prompt? This part introduces the definition and examples of prompt.This part of the content can be listened to for free。

Part 2: Why should we write a good prompt? This part introduces the importance of prompt.This part of the content can be listened to for free。

Part 3: Basic writing methods of prompt. This part introduces the basics of prompt, including basic writing thinking, incorrect writing cases, ICIO framework, APE framework, BROKE framework, ROSES framework, SCOPE framework and other writing frameworks.

Part 4: Advanced writing skills for prompts. This part introduces some methods to improve prompt words, including making good use of separators to improve readability, structured output results, user input integrity check, iterative optimization of prompts, built-in knowledge base to solve model illusions, nesting dolls - defeating magic with magic, cot - let the model analyze step by step, and self-consistency - let the model calculate multiple times.

Part 5: Practical application of the Air Ticket Assistant prompt project. This part of the course will lead you to implement an air ticket assistant from scratch based on Zhipu Qingyan's API.

This course is a recorded course, the instructorDi Yun, an NLP algorithm expert at a Fortune 500 company, a lecturer for three AI online courses, has published many international conference papers, and holds more than 10 patents.

How to Subscribe

All our video courses are on the Xiaoetong platform. You can use the Xiaoetong mobile app or log in directly on the web page. To listen to the content and subscribe, please scan the following QR code:

Course details are as follows:

More practical course content

For more practical project course content, please refer to our practical project course collection as follows:

[One-to-one group] Three AI-CV advanced-project practice groups will be released in 2024, with more than 30 cases and 60 hours of project practice

Recruitment of practical course instructors

In order to further enrich the practical content of Yousan AI Ecosystem, experienced and capable lecturers are welcome to sign up to become platform lecturers:

The lecturer requirements are as follows:

(1) Has multiple teaching experiences in the field of artificial intelligence and is good at public speaking and teaching.

(2) Have more than 3 years of practical experience in artificial intelligence projects.

(3) Priority will be given to existing members of the three AI ecosystems.

The income of practical courses and the platformFixed shareFor details, please contact the content group.WeChat-LonglongtogoSubmit your resume or send an email to [email protected].

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