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Heng-Shiou Sheu 許恆修
歡迎來到 Udemy 課程上第一堂中文 LangChain 課程！
本全面的課程旨在教授你如何運用 LangChain 力量並實踐於 LLM 領域。此課程將為您提供所需的技能和知識，好為各種主題開發生活中常見的的 LLM 解決方案。
在本課程中，你將從零開始，使用 LangChain 打造多個務實的 LLM 應用程式。從跟你的文件聊天、總結 Yotube 影片內容到使用 Agent 跟 Excel 聊天。你將透過大量練習以及打造實際專案，了解各種 LLM 解決方案。
本課程涵蓋的主題包括：
介紹 LangChain
LangChain 必備模組介紹
Prompt: PromptTemplate
LLM: OpenAI
Chain: LLMChain、RetrievalQA Chain、QA Chain
Agent: create_csv_agent
Tools: llm_math, serpapi
Memory: conversationalBufferMemory
向量資料庫：Pinecone、Chroma
本課程實作專案主題：
與你的文件聊天，實作 DocGPT
Read more
歡迎來到 Udemy 課程上第一堂中文 LangChain 課程！
本全面的課程旨在教授你如何運用 LangChain 力量並實踐於 LLM 領域。此課程將為您提供所需的技能和知識，好為各種主題開發生活中常見的的 LLM 解決方案。
在本課程中，你將從零開始，使用 LangChain 打造多個務實的 LLM 應用程式。從跟你的文件聊天、總結 Yotube 影片內容到使用 Agent 跟 Excel 聊天。你將透過大量練習以及打造實際專案，了解各種 LLM 解決方案。
本課程涵蓋的主題包括：
介紹 LangChain
LangChain 必備模組介紹
Prompt: PromptTemplate
LLM: OpenAI
Chain: LLMChain、RetrievalQA Chain、QA Chain
Agent: create_csv_agent
Tools: llm_math, serpapi
Memory: conversationalBufferMemory
向量資料庫：Pinecone、Chroma
本課程實作專案主題：
與你的文件聊天，實作 DocGPT
Read more
歡迎來到 Udemy 課程上第一堂中文 LangChain 課程！
本全面的課程旨在教授你如何運用 LangChain 力量並實踐於 LLM 領域。此課程將為您提供所需的技能和知識，好為各種主題開發生活中常見的的 LLM 解決方案。
在本課程中，你將從零開始，使用 LangChain 打造多個務實的 LLM 應用程式。從跟你的文件聊天、總結 Yotube 影片內容到使用 Agent 跟 Excel 聊天。你將透過大量練習以及打造實際專案，了解各種 LLM 解決方案。
本課程涵蓋的主題包括：
介紹 LangChain
LangChain 必備模組介紹
Prompt: PromptTemplate
LLM: OpenAI
Chain: LLMChain、RetrievalQA Chain、QA Chain
Agent: create_csv_agent
Tools: llm_math, serpapi
Memory: conversationalBufferMemory
向量資料庫：Pinecone、Chroma
本課程實作專案主題：
與你的文件聊天，實作 DocGPT
總結 Youtube 談話資訊，實作 YoutubeGPT
在整個課程中，您將進行實作練習和實際項目，以加深您對所涵蓋概念和技術的理解。課程結束時，您將熟練使用 LangChain 為各種用途創建功能強大，高效且多功能的 LLM 應用程式。
Register for this course and see more details by visiting:
OpenCourser.com/course/w8y70c/Jin
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What's inside
Syllabus
學員在這個章節結束後，將會知曉 LLM 概念，並且知道如何善用 LangChain 實作自己的 LLM 應用程式。
課程介紹
學生在這個章節中，可以學習到如何取得 OpenAI API Key，好建立後續 LLM 應用程式
章節介紹
Read more
Syllabus
學員在這個章節結束後，將會知曉 LLM 概念，並且知道如何善用 LangChain 實作自己的 LLM 應用程式。
課程介紹
學生在這個章節中，可以學習到如何取得 OpenAI API Key，好建立後續 LLM 應用程式
章節介紹
Read more
OpenAI Api Key 申請
Pinecone Key 申請
SerpApi: Google Search API 申請
課程專案 - Github Repo 連結
學生學習玩這們課程後，能夠對於 Langchain 具有哪些模組有個初步概念，並且透過練習，具體了解 LLM, Prompt, Chains, Agents, Memory 模組用途
Models 模組 - 透過 LLM 取得摘要、推理、生成能力
Prompt 模組 - 替 LLM 管理提示語
Chain 模組 - 結合 LLM 與 prompts 於多個步驟工作流中
Agent 模組 - 讓 LLM 選擇要用的 tool 解決問題
Memory 模組 - 賦予 Chains 與 Agents 記憶
實作篇：跟你的文件講話 - 實作 DocGPT
專案介紹
套件安裝與環境設置
讀取 PDF 文件的多種方法：PyPDF2, PyPDFLoader, PyMuPDFLoader
使用 qa_chain 與文件對話，同時認識不同 chain_type：stuff, map_reduce
文件太大時怎麼辦？請找 RecursiveCharacterTextSplitter
向量化文件，並且存放至向量資料庫 Chroma 中
多種使用 Chain 與文件對話的方式：RetrievalQA, ConversationalRetrievalChain
實作篇：不只娛樂，還能玩樂 - 實作 YoutubeGPT
讀取 Youtube 影片
字幕呢？你需要的是 Whisper
該呼叫 Chain 上場了：load_summarize_chain
想要其他總結方式？你需要的是 Prompt
實作篇：解放 Excel 表格 - 實作表格GPT
讀取 CSV 檔案
存放向量至向量資料庫 Chroma
建構 QAChain 進行問答
建構 Agent 進行問答
Agent 是一個推理引擎，旨在做出決策、選擇工具並採取行動以實現特定的目標。Agent 自主運行，很少需要人工干預其操作。 強大工具以及自力更生，使得 Agent 吸引了如此多的注意力，值得熟悉這項技術。本章節中，將帶領各位學員，如何熟練掌握 Agent 使用技巧與知識 。
章節起頭：重新認識 Agent
Agent 基礎認識
慢著，Agent 與 Chain 有何不同？
認識 Agent 種類 - zero shot
認識 Agent 種類 - Chat Conversational ReAct
認識 Agent 種類 - ReAct Doc store
自定義 Tool - 利用 BaseTool 實作
自定義 Tool - 用於接收多個參數
添加 HuggingFace model 作為 Tool 使用 - BLIP 模型做示範
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Emphasizes using LangChain, a tool popular in industry
Instructs learners in applying LLM technologies to diverse settings, fostering adaptability and problem-solving skills
Features expert instructors Heng-Shiou Sheu 許恆修, known for their contributions to the field
Useful for those seeking to build LLM applications in various domains
Requires learners to have some foundational knowledge in LLM and programming
This course is fully taught in Chinese
Save this course
Save 進擊的 LangChain 學習路：打造 LLM 驅動應用程式的必備技能，一步步教你如何開發 AI 應用專案 to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in 進擊的 LangChain 學習路：打造 LLM 驅動應用程式的必備技能，一步步教你如何開發 AI 應用專案 with these
activities:
回顧 Python 基礎
Show steps
複習 Python 基礎可以幫助你更輕鬆地理解 LangChain 的程式碼和 API。
Browse courses on
Python
Show steps
-
回顧 Python 的基本資料型態，如字串、數字和清單
-
練習使用 Python 的控制結構，如 if-else 陳述式和迴圈
-
回顧 Python 的函式和模組
Review vectors and matrices
Show steps
Familiarity with vectors and matrices is necessary to understand the concepts of LLM.
Browse courses on
Vectors
Show steps
-
Review lecture notes from previous course or textbook.
-
Work through practice problems.
-
Take a practice quiz.
隨從 LangChain 團隊的 Youtube 頻道
Show steps
LangChain 團隊的 Youtube 頻道提供許多使用 LangChain 的教學影片，觀看這些影片可以幫助你深入了解 LangChain 的功能和應用。
Show steps
-
訂閱 LangChain 的 Youtube 頻道
-
觀看 LangChain 團隊上傳的教學影片
-
在影片下方留言詢問問題或分享你的見解
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Attend a workshop on LLM and LangChain.
Show steps
Attending a workshop will help you learn more about LLM and LangChain from experts in the field.
Show steps
-
Find a workshop on LLM and LangChain that is relevant to your interests and learning goals.
-
Register for the workshop.
-
Attend the workshop and participate in the activities.
-
Take notes and ask questions during the workshop.
加入 LangChain 學習社群
Show steps
加入 LangChain 學習社群可以讓你與其他學習者和專家交流，並從他們的經驗中學習。
Show steps
-
加入 LangChain 的 Discord 伺服器
-
參加 LangChain 社群舉辦的活動和工作坊
-
在 LangChain 論壇上發布問題和分享你的見解
Create a collection of LLM resources
Show steps
Creating a resource collection will help you organize and consolidate information about LLM.
Show steps
-
Gather resources from various sources, such as articles, blog posts, videos, and tutorials.
-
Create a document or website to store the resources.
-
Categorize and organize the resources for easy access.
練習使用 LangChain 的 API
Show steps
練習使用 LangChain 的 API 可以幫助你熟悉 LangChain 的工作原理，並提高你開發 LLM 應用程式的能力。
Show steps
-
取得 LangChain 的 API 密鑰
-
使用 Python 或其他程式語言編寫程式碼來呼叫 LangChain 的 API
-
嘗試使用 LangChain 的不同模組和功能
Practice using LangChain on sample data
Show steps
Practice will help you become more proficient in using LangChain.
Show steps
-
Follow along with the tutorials in the course.
-
Use the LangChain playground to experiment with different prompts and settings.
-
Complete the practice exercises at the end of each chapter.
建立一個使用 LangChain 的個人專案
Show steps
建立一個使用 LangChain 的個人專案可以讓你實際應用你在課程中學到的知識，並深入了解 LLM 應用程式的開發。
Show steps
-
想出一個使用 LangChain 來解決問題或自動化任務的點子
-
設計你的專案架構並選擇要使用的 LangChain 模組
-
實作你的專案並測試它的功能
-
部署你的專案並與他人分享
建立一個多模 LLM 聊天機器人
Show steps
建立一個多模 LLM 聊天機器人可以讓你實際應用你在課程中學到的知識，並深入了解如何使用 LLM 來處理自然語言。
Show steps
-
選擇一個 LLM 提供商，例如 OpenAI 或 Google
-
設計你的聊天機器人的架構和功能
-
實作你的聊天機器人並訓練它使用 LLM 模型
-
部署你的聊天機器人並與他人分享
Build a simple LLM application.
Show steps
Building an application will help you apply your knowledge of LangChain and LLM.
Show steps
-
Choose a simple application idea, such as a chatbot or a text summarizer.
-
Design the application's interface and functionality.
-
Implement the application using LangChain and LLM.
-
Test the application and make any necessary adjustments.
Create a presentation on your LLM application.
Show steps
Creating a presentation will help you consolidate your knowledge of LLM and LangChain.
Show steps
-
Outline the key features and benefits of your application.
-
Develop a storyboard for your presentation.
-
Create slides for your presentation.
-
Practice delivering your presentation.
Participate in a hackathon or competition that uses LLM
Show steps
Participating in a hackathon or competition will challenge you to apply your skills and knowledge of LLM and LangChain in a real-world setting.
Show steps
-
Find a hackathon or competition that uses LLM.
-
Form a team or work on your own.
-
Develop a project idea and build an LLM application.
-
Submit your project and compete for prizes.
Contribute to the LangChain open-source project.
Show steps
Contributing to the LangChain open-source project will help you learn more about LLM and LangChain and contribute to the community.
Show steps
-
Find an issue on the LangChain GitHub repository that you are interested in working on.
-
Fork the LangChain repository and create a branch for your changes.
-
Make your changes and submit a pull request.
-
Respond to feedback from the LangChain maintainers.
Mentor other students who are learning about LLM and LangChain.
Show steps
Mentoring other students will help you deepen your understanding of LLM and LangChain and give back to the community.
Show steps
-
Join a community or forum where students can ask questions about LLM and LangChain.
-
Offer your help to students who are struggling.
-
Share your knowledge and experience with other students.
-
Encourage and support other students in their learning journey.
回顧 Python 基礎
Show steps
複習 Python 基礎可以幫助你更輕鬆地理解 LangChain 的程式碼和 API。
Browse courses on
Python
Show steps
Show steps
Show steps
- 回顧 Python 的基本資料型態，如字串、數字和清單
- 練習使用 Python 的控制結構，如 if-else 陳述式和迴圈
- 回顧 Python 的函式和模組
Review vectors and matrices
Show steps
Familiarity with vectors and matrices is necessary to understand the concepts of LLM.
Browse courses on
Vectors
Show steps
Show steps
Show steps
- Review lecture notes from previous course or textbook.
- Work through practice problems.
- Take a practice quiz.
隨從 LangChain 團隊的 Youtube 頻道
Show steps
LangChain 團隊的 Youtube 頻道提供許多使用 LangChain 的教學影片，觀看這些影片可以幫助你深入了解 LangChain 的功能和應用。
Show steps
Show steps
Show steps
- 訂閱 LangChain 的 Youtube 頻道
- 觀看 LangChain 團隊上傳的教學影片
- 在影片下方留言詢問問題或分享你的見解
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Attend a workshop on LLM and LangChain.
Show steps
Attending a workshop will help you learn more about LLM and LangChain from experts in the field.
Show steps
Show steps
Show steps
- Find a workshop on LLM and LangChain that is relevant to your interests and learning goals.
- Register for the workshop.
- Attend the workshop and participate in the activities.
- Take notes and ask questions during the workshop.
加入 LangChain 學習社群
Show steps
加入 LangChain 學習社群可以讓你與其他學習者和專家交流，並從他們的經驗中學習。
Show steps
Show steps
Show steps
- 加入 LangChain 的 Discord 伺服器
- 參加 LangChain 社群舉辦的活動和工作坊
- 在 LangChain 論壇上發布問題和分享你的見解
Create a collection of LLM resources
Show steps
Creating a resource collection will help you organize and consolidate information about LLM.
Show steps
Show steps
Show steps
- Gather resources from various sources, such as articles, blog posts, videos, and tutorials.
- Create a document or website to store the resources.
- Categorize and organize the resources for easy access.
練習使用 LangChain 的 API
Show steps
練習使用 LangChain 的 API 可以幫助你熟悉 LangChain 的工作原理，並提高你開發 LLM 應用程式的能力。
Show steps
Show steps
Show steps
- 取得 LangChain 的 API 密鑰
- 使用 Python 或其他程式語言編寫程式碼來呼叫 LangChain 的 API
- 嘗試使用 LangChain 的不同模組和功能
Practice using LangChain on sample data
Show steps
Practice will help you become more proficient in using LangChain.
Show steps
Show steps
Show steps
- Follow along with the tutorials in the course.
- Use the LangChain playground to experiment with different prompts and settings.
- Complete the practice exercises at the end of each chapter.
建立一個使用 LangChain 的個人專案
Show steps
建立一個使用 LangChain 的個人專案可以讓你實際應用你在課程中學到的知識，並深入了解 LLM 應用程式的開發。
Show steps
Show steps
Show steps
- 想出一個使用 LangChain 來解決問題或自動化任務的點子
- 設計你的專案架構並選擇要使用的 LangChain 模組
- 實作你的專案並測試它的功能
- 部署你的專案並與他人分享
建立一個多模 LLM 聊天機器人
Show steps
建立一個多模 LLM 聊天機器人可以讓你實際應用你在課程中學到的知識，並深入了解如何使用 LLM 來處理自然語言。
Show steps
Show steps
Show steps
- 選擇一個 LLM 提供商，例如 OpenAI 或 Google
- 設計你的聊天機器人的架構和功能
- 實作你的聊天機器人並訓練它使用 LLM 模型
- 部署你的聊天機器人並與他人分享
Build a simple LLM application.
Show steps
Building an application will help you apply your knowledge of LangChain and LLM.
Show steps
Show steps
Show steps
- Choose a simple application idea, such as a chatbot or a text summarizer.
- Design the application's interface and functionality.
- Implement the application using LangChain and LLM.
- Test the application and make any necessary adjustments.
Create a presentation on your LLM application.
Show steps
Creating a presentation will help you consolidate your knowledge of LLM and LangChain.
Show steps
Show steps
Show steps
- Outline the key features and benefits of your application.
- Develop a storyboard for your presentation.
- Create slides for your presentation.
- Practice delivering your presentation.
Participate in a hackathon or competition that uses LLM
Show steps
Participating in a hackathon or competition will challenge you to apply your skills and knowledge of LLM and LangChain in a real-world setting.
Show steps
Show steps
Show steps
- Find a hackathon or competition that uses LLM.
- Form a team or work on your own.
- Develop a project idea and build an LLM application.
- Submit your project and compete for prizes.
Contribute to the LangChain open-source project.
Show steps
Contributing to the LangChain open-source project will help you learn more about LLM and LangChain and contribute to the community.
Show steps
Show steps
Show steps
- Find an issue on the LangChain GitHub repository that you are interested in working on.
- Fork the LangChain repository and create a branch for your changes.
- Make your changes and submit a pull request.
- Respond to feedback from the LangChain maintainers.
Mentor other students who are learning about LLM and LangChain.
Show steps
Mentoring other students will help you deepen your understanding of LLM and LangChain and give back to the community.
Show steps
Show steps
Show steps
- Join a community or forum where students can ask questions about LLM and LangChain.
- Offer your help to students who are struggling.
- Share your knowledge and experience with other students.
- Encourage and support other students in their learning journey.
Career center
Learners who complete 進擊的 LangChain 學習路：打造 LLM 驅動應用程式的必備技能，一步步教你如何開發 AI 應用專案 will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer designs and builds systems that understand and process human language. LangChain is a tool purpose-built for NLP tasks. This course provides a comprehensive overview of how LangChain can be used for NLP tasks.
Data Scientist
Data Scientist
A Data Scientist analyzes data and builds ML models to solve business problems. LangChain is a powerful tool that Data Scientists can use to build LLM-based models. This course will set you up for success by teaching the LangChain workflow.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs and builds scalable ML models and systems. This course's introduction to LLMChains, which are a type of ML model, is a great starting point for aspiring Machine Learning Engineers.
Computational Linguist
Computational Linguist
A Computational Linguist studies the relationship between language and computation. This course teaches LangChain, a tool that can be used to build LLM-based applications. This makes it a great fit for Computational Linguists who want to learn more about LLM applications.
Software Engineer
Software Engineer
A Software Engineer designs, develops, deploys, and maintains software applications. LangChain, which this course teaches, can help software engineers get started with developing LLM applications by providing the basic building blocks and tools needed to do so.
AI Researcher
AI Researcher
An AI Researcher develops new AI algorithms and techniques. This course teaches the fundamentals of LLMChains and how to use LangChain to build LLM-based applications. This will help build a foundation for an AI Researcher.
Business Analyst
Business Analyst
A Business Analyst analyzes business processes and develops solutions to improve efficiency. This course can help Business Analysts learn how to use LLMChains to build LLM-based applications that can improve business processes.
Product Manager
Product Manager
A Product Manager manages the development and launch of new products. This course teaches the fundamentals of LLMChains and how to use LangChain to build LLM-based applications. This knowledge can be used by Product Managers to develop LLM-based products.
Marketing Manager
Marketing Manager
A Marketing Manager develops and executes marketing campaigns. This course will help build a foundation for Marketing Managers who want to learn how to use LLMs to improve their marketing campaigns.
Management Consultant
Management Consultant
A Management Consultant provides advice to businesses on how to improve their operations. This course teaches the fundamentals of LLMChains and how to use LangChain to build LLM-based applications. This knowledge can be used by Management Consultants to advise businesses on how to use LLMs to improve their operations.
Technical Support Specialist
Technical Support Specialist
A Technical Support Specialist provides technical support to users of software and hardware. This course may be useful for Technical Support Specialists who want to learn how to use LLMs to improve their support.
UI Designer
UI Designer
A UI Designer designs and evaluates user interfaces. This course may be useful for UI Designers who want to learn how to use LLMs to improve user interfaces.
Content Writer
Content Writer
A Content Writer creates and edits written content. This course may be useful for Content Writers who want to learn how to use LLMs to improve their writing.
UX Designer
UX Designer
A UX Designer designs and evaluates user experiences. This course may be useful for UX Designers who want to learn how to use LLMs to improve user experiences.
Technical Writer
Technical Writer
A Technical Writer creates and edits technical documentation. This course may be useful for Technical Writers who want to learn how to use LLMs to improve their documentation.
For more career information including salaries, visit:
OpenCourser.com/course/w8y70c/Jin
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
進擊的 LangChain 學習路：打造 LLM 驅動應用程式的必備技能，一步步教你如何開發 AI 應用專案.
Provides a comprehensive introduction to deep learning, covering the fundamental concepts, algorithms, and applications. It valuable resource for anyone who wants to learn about the basics of deep learning.
Provides a practical guide to deep learning with Python, covering the essential concepts, algorithms, and applications. It valuable resource for anyone who wants to learn about the basics of deep learning.
Provides a comprehensive overview of natural language processing, covering the fundamental concepts, algorithms, and applications. It valuable resource for anyone who wants to learn about the basics of natural language processing.
Provides a comprehensive overview of speech and language processing, covering the fundamental concepts, algorithms, and applications. It valuable resource for anyone who wants to learn about the basics of speech and language processing.
Provides a comprehensive overview of the Natural Language Toolkit (NLTK), a popular Python library for natural language processing. It valuable resource for anyone who wants to learn about the basics of natural language processing.
Provides a comprehensive overview of natural language processing in action, covering the fundamental concepts, algorithms, and applications. It valuable resource for anyone who wants to learn about the basics of natural language processing in action.
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Effort
3 total hours
Via
Udemy
Instructor
Heng-Shiou Sheu 許恆修
Language
中文
Good to know
Emphasizes using LangChain, a tool popular in industry
Instructs learners in applying LLM technologies to diverse settings, fostering adaptability and problem-solving skills
Features expert instructors Heng-Shiou Sheu 許恆修, known for their contributions to the field
Useful for those seeking to build LLM applications in various domains
Requires learners to have some foundational knowledge in LLM and programming
This course is fully taught in Chinese
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