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Greg Lim
In this short course, we take you on a fun, hands-on and pragmatic journey to learn how to build LLM powered apps using LangChain. You'll start building your first Generative AI app within minutes. Every section is recorded in a bite-sized manner and straight to the point as I don’t want to waste your time (and most certainly mine) on the content you don't need.
Read more
In this short course, we take you on a fun, hands-on and pragmatic journey to learn how to build LLM powered apps using LangChain. You'll start building your first Generative AI app within minutes. Every section is recorded in a bite-sized manner and straight to the point as I don’t want to waste your time (and most certainly mine) on the content you don't need.
Read more
In this short course, we take you on a fun, hands-on and pragmatic journey to learn how to build LLM powered apps using LangChain. You'll start building your first Generative AI app within minutes. Every section is recorded in a bite-sized manner and straight to the point as I don’t want to waste your time (and most certainly mine) on the content you don't need.
In this course, we will cover:
What is LangChain
How does LangChain Work
Installation, Setup and Our First LangChain App
Building a Medium Article Generator App
Connecting to OpenAI LLM
Prompt Templates
Simple Chains
Sequential Chains
Agents
Chat with a Document
Adding Memory (Chat History)
Outputting the Chat History
Uploading Custom Documents
Loading Different Document Types (eg PDF, txt, docs)
Chat with Youtube and more...
The goal of this course is to teach you LangChain development in a manageable way without overwhelming you. We focus only on the essentials and cover the material in a hands-on practice manner for you to code along.
Working Through This Course
This course is purposely broken down into short sections where the development process of each section will center on different essential topics. The course a practical hands on approach to learning through practice. You learn best when you code along with the examples.
Register for this course and see more details by visiting:
OpenCourser.com/course/9c6ye5/langchain
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What's inside
Learning objectives
- Learn key langchain features like connecting to openai llms, prompt templates, chains, document loaders, agents, memory
- Learn how to build a medium article generator and a question & answer document chatbot
- Build practical hands-on project without all the fluff
- Learn langchain even if you are a beginner in a weekend
- Learn key langchain features like connecting to openai llms, prompt templates, chains, document loaders, agents, memory
- Learn how to build a medium article generator and a question & answer document chatbot
- Build practical hands-on project without all the fluff
- Learn langchain even if you are a beginner in a weekend
Syllabus
Introduction
What is LangChain
How does LangChain work
Build a Medium Article Generator App
Read more
Syllabus
Introduction
What is LangChain
How does LangChain work
Build a Medium Article Generator App
Read more
What we will be building
Installation, Setup and Our First LangChain App
Connecting to OpenAI LLM
Prompt Templates
Simple Chains
Sequential Chains
Agents
Build a Question & Answer PDF, Txt, Docx Document Chatbot
Chat with a Document
Adding Memory (Chat History)
Outputting the Chat History
Uploading Custom Documents
Loading Different File Types
Chat with Youtube
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for beginners and those looking to learn LangChain development in a weekend
Provides a practical hands-on approach to learning LangChain development
Develops key skills in connecting to OpenAI LLMs, using prompt templates, and creating simple and sequential chains
Covers real-world applications, such as building a Medium article generator and a question & answer PDF document chatbot
Save this course
Save LangChain Crash Course: Build OpenAI LLM powered Apps to your list so you can find it easily later:
Save
Save
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 LangChain Crash Course: Build OpenAI LLM powered Apps with these
activities:
Review how LLMs work
Show steps
Reviewing key concepts of LLMs can solidify your understanding before beginning the course.
Browse courses on
LLM
Show steps
-
Define what an LLM is in your own words
-
Describe the different types of LLMs
-
Explain the benefits and limitations of using LLMs
Seek out a mentor who can provide guidance and support on your LLM development journey
Show steps
Having a mentor can provide valuable insights and guidance as you progress in your LLM development skills.
Show steps
-
Identify potential mentors in the LLM field
-
Reach out to these mentors and request their guidance
-
Meet with your mentor regularly to discuss your progress and seek advice
Follow a tutorial on building a simple chatbot using LangChain
Show steps
Going through a tutorial on a specific LLM application can provide practical context for the course material.
Browse courses on
LangChain
Show steps
-
Find a tutorial on building a chatbot using LangChain
-
Follow the tutorial to build a basic chatbot
-
Experiment with different parameters and settings in the chatbot
Five other activities
Expand to see all activities and additional details
Show all eight activities
Code along with the examples in the course
Show steps
Hands-on practice is crucial for solidifying your understanding of LangChain.
Show steps
-
Set up your development environment
-
Code along with the examples in each section
-
Experiment with different parameters and settings in the code
Mentor other students or beginners who are learning LangChain
Show steps
Mentoring others can help you solidify your understanding of LangChain and identify areas where you need more clarification.
Show steps
-
Find students or beginners who are learning LangChain
-
Provide guidance and support to these students
-
Answer their questions and help them troubleshoot problems
Create a blog post summarizing the key concepts of LangChain
Show steps
Summarizing and explaining LLM concepts in your own words can deepen your understanding and identify areas where you need more clarification.
Show steps
-
Review the key concepts of LangChain
-
Write a blog post summarizing the key concepts in your own words
-
Share your blog post with others for feedback
Build a chatbot that can answer questions about a specific topic
Show steps
Applying your skills to a practical project can demonstrate your understanding of LangChain and showcase your abilities.
Show steps
-
Choose a specific topic for your chatbot
-
Design the architecture of your chatbot
-
Develop the chatbot using LangChain
-
Test and refine your chatbot
Participate in a hackathon or competition that involves building LLM applications
Show steps
Participating in a hackathon or competition can provide valuable experience and challenge you to apply your skills in a real-world setting.
Show steps
-
Find a hackathon or competition that involves building LLM applications
-
Form a team or work individually on a project
-
Develop and submit your LLM application
Review how LLMs work
Show steps
Reviewing key concepts of LLMs can solidify your understanding before beginning the course.
Browse courses on
LLM
Show steps
Show steps
Show steps
- Define what an LLM is in your own words
- Describe the different types of LLMs
- Explain the benefits and limitations of using LLMs
Seek out a mentor who can provide guidance and support on your LLM development journey
Show steps
Having a mentor can provide valuable insights and guidance as you progress in your LLM development skills.
Show steps
Show steps
Show steps
- Identify potential mentors in the LLM field
- Reach out to these mentors and request their guidance
- Meet with your mentor regularly to discuss your progress and seek advice
Follow a tutorial on building a simple chatbot using LangChain
Show steps
Going through a tutorial on a specific LLM application can provide practical context for the course material.
Browse courses on
LangChain
Show steps
Show steps
Show steps
- Find a tutorial on building a chatbot using LangChain
- Follow the tutorial to build a basic chatbot
- Experiment with different parameters and settings in the chatbot
Five other activities
Expand to see all activities and additional details
Show all eight activities
Code along with the examples in the course
Show steps
Hands-on practice is crucial for solidifying your understanding of LangChain.
Show steps
Show steps
Show steps
- Set up your development environment
- Code along with the examples in each section
- Experiment with different parameters and settings in the code
Mentor other students or beginners who are learning LangChain
Show steps
Mentoring others can help you solidify your understanding of LangChain and identify areas where you need more clarification.
Show steps
Show steps
Show steps
- Find students or beginners who are learning LangChain
- Provide guidance and support to these students
- Answer their questions and help them troubleshoot problems
Create a blog post summarizing the key concepts of LangChain
Show steps
Summarizing and explaining LLM concepts in your own words can deepen your understanding and identify areas where you need more clarification.
Show steps
Show steps
Show steps
- Review the key concepts of LangChain
- Write a blog post summarizing the key concepts in your own words
- Share your blog post with others for feedback
Build a chatbot that can answer questions about a specific topic
Show steps
Applying your skills to a practical project can demonstrate your understanding of LangChain and showcase your abilities.
Show steps
Show steps
Show steps
- Choose a specific topic for your chatbot
- Design the architecture of your chatbot
- Develop the chatbot using LangChain
- Test and refine your chatbot
Participate in a hackathon or competition that involves building LLM applications
Show steps
Participating in a hackathon or competition can provide valuable experience and challenge you to apply your skills in a real-world setting.
Show steps
Show steps
Show steps
- Find a hackathon or competition that involves building LLM applications
- Form a team or work individually on a project
- Develop and submit your LLM application
Career center
Learners who complete LangChain Crash Course: Build OpenAI LLM powered Apps will develop knowledge and skills
that may be useful to these careers:
Developer Evangelist
Developer Evangelist
Developer Evangelists promote and educate developers on new technologies, such as large language models (LLMs) and Generative AI. LangChain is a platform that enables developers to build LLM-powered applications. This course provides a comprehensive introduction to LangChain, covering key concepts such as connecting to OpenAI LLMs, building chains, and adding memory. By learning LangChain, you can develop in-demand skills that can help you succeed as a Developer Evangelist.
ML Engineer
ML Engineer
ML Engineers are responsible for designing, developing, and maintaining machine learning models. LangChain is a powerful tool for ML Engineers, enabling them to quickly and easily build and deploy LLM-powered applications. This course provides a solid foundation in LangChain, covering topics such as prompt templates, agents, and chat with documents. By completing this course, you will gain the skills necessary to use LangChain to create innovative ML applications.
AI Researcher
AI Researcher
AI Researchers are involved in the development of new AI technologies, including LLMs. LangChain is a valuable platform for AI Researchers, enabling them to experiment with and test new LLM applications. This course provides a comprehensive overview of LangChain, covering advanced topics such as sequential chains, custom documents, and different file types. By taking this course, you will gain the knowledge and skills necessary to conduct cutting-edge AI research using LangChain.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. LangChain can be used to analyze data and generate insights. This course provides a practical introduction to LangChain, covering topics such as connecting to OpenAI LLMs, prompt templates, and simple chains. By learning LangChain, you can expand your skillset and become a more effective Data Scientist.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. LangChain is a powerful platform for building LLM-powered applications. This course provides a comprehensive introduction to LangChain, covering topics such as installation, setup, and building your first app. By completing this course, you will gain the skills necessary to develop innovative software applications using LangChain.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. LangChain can be used to develop prototypes and gather feedback from users. This course provides a practical introduction to LangChain, covering topics such as building a Medium Article Generator app and a Question & Answer Document Chatbot. By learning LangChain, you can gain the skills necessary to develop and launch successful products.
UX Researcher
UX Researcher
UX Researchers study how users interact with products and services. LangChain can be used to gather feedback from users and improve the user experience. This course provides a practical introduction to LangChain, covering topics such as chat with a document and adding memory. By learning LangChain, you can gain the skills necessary to conduct user research and improve the user experience of your products.
Business Analyst
Business Analyst
Business Analysts analyze business processes and identify areas for improvement. LangChain can be used to automate tasks and improve efficiency. This course provides a practical introduction to LangChain, covering topics such as agents and sequential chains. By learning LangChain, you can gain the skills necessary to improve business processes and make your organization more efficient.
Technical Writer
Technical Writer
Technical Writers create documentation for software and other technical products. LangChain can be used to generate documentation and keep it up to date. This course provides a practical introduction to LangChain, covering topics such as outputting the chat history and uploading custom documents. By learning LangChain, you can gain the skills necessary to create and maintain high-quality technical documentation.
Instructional Designer
Instructional Designer
Instructional Designers develop and deliver training programs. LangChain can be used to create interactive training materials and simulations. This course provides a practical introduction to LangChain, covering topics such as building a Medium Article Generator app and a Question & Answer Document Chatbot. By learning LangChain, you can gain the skills necessary to create and deliver engaging training programs.
Customer Success Manager
Customer Success Manager
Customer Success Managers help customers get the most value from a product or service. LangChain can be used to provide customer support and resolve issues. This course provides a practical introduction to LangChain, covering topics such as chat with a document and adding memory. By learning LangChain, you can gain the skills necessary to provide excellent customer support.
Sales Engineer
Sales Engineer
Sales Engineers help customers understand and purchase technical products. LangChain can be used to create demos and presentations. This course provides a practical introduction to LangChain, covering topics such as building a Medium Article Generator app and a Question & Answer Document Chatbot. By learning LangChain, you can gain the skills necessary to create and deliver effective sales presentations.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns. LangChain can be used to create marketing content and generate leads. This course provides a practical introduction to LangChain, covering topics such as building a Medium Article Generator app and a Question & Answer Document Chatbot. By learning LangChain, you can gain the skills necessary to create and execute successful marketing campaigns.
Project Manager
Project Manager
Project Managers plan and execute projects. LangChain can be used to manage tasks and track progress. This course provides a practical introduction to LangChain, covering topics such as agents and sequential chains. By learning LangChain, you can gain the skills necessary to plan and execute projects more effectively.
Consultant
Consultant
Consultants provide advice and guidance to businesses. LangChain can be used to gather data and analyze trends. This course provides a practical introduction to LangChain, covering topics such as connecting to OpenAI LLMs and prompt templates. By learning LangChain, you can gain the skills necessary to provide valuable insights to your clients.
For more career information including salaries, visit:
OpenCourser.com/course/9c6ye5/langchain
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
LangChain Crash Course: Build OpenAI LLM powered Apps.
Save
This handbook provides a comprehensive and in-depth coverage of NLP. While it may not specifically focus on LLM-based applications, it offers a comprehensive reference for understanding the theory and techniques behind NLP, which can be valuable for those looking to build a deeper understanding of the underlying technology.
Provides an overview of language models, their history, and their applications. It covers topics like language model architectures, training techniques, and evaluation metrics, which are fundamental for understanding and building LLM-based systems.
Offers a comprehensive overview of deep learning approaches to NLP. It covers topics like word embeddings, neural networks, and transformers, which are essential for understanding the technical foundations of LLMs and how they are used in practical applications.
Offers a practical approach to NLP, focusing on real-world application development. It covers essential concepts and provides step-by-step guidance for building NLP-powered solutions, which can be beneficial for those who want to implement LLM-based applications.
Is considered a classic in machine learning and provides a comprehensive introduction to statistical learning techniques. While it may not focus specifically on NLP or LLMs, it offers a solid foundation in statistical concepts and methods that are essential for understanding and working with LLM-based applications.
Provides a comprehensive introduction to natural language processing (NLP), covering fundamental concepts and techniques. While it may not directly cover LangChain, NLP is the foundation for many of the functionalities offered by LLMs.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9c6ye5/langchain
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Effort
1.5 total hours
Via
Udemy
Instructor
Greg Lim
Language
English
Good to know
Suitable for beginners and those looking to learn LangChain development in a weekend
Provides a practical hands-on approach to learning LangChain development
Develops key skills in connecting to OpenAI LLMs, using prompt templates, and creating simple and sequential chains
Covers real-world applications, such as building a Medium article generator and a question & answer PDF document chatbot
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