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Harrison Chase
and
Andrew Ng
In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.
In this course you will learn and get experience with the following topics:
1. Models, Prompts and Parsers: Calling LLMs, providing prompts and parsing the response.
2. Memories for LLMs: Memories to store conversations and manage limited context space.
3. Chains: Creating sequences of operations.
Read more
In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.
In this course you will learn and get experience with the following topics:
1. Models, Prompts and Parsers: Calling LLMs, providing prompts and parsing the response.
2. Memories for LLMs: Memories to store conversations and manage limited context space.
3. Chains: Creating sequences of operations.
Read more
In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.
In this course you will learn and get experience with the following topics:
1. Models, Prompts and Parsers: Calling LLMs, providing prompts and parsing the response.
2. Memories for LLMs: Memories to store conversations and manage limited context space.
3. Chains: Creating sequences of operations.
4. Question Answering over Documents: Apply LLMs to your proprietary data and use case requirements.
5. Agents: Explore the powerful emerging development of LLM as reasoning agents.
At the end of the course, you will have a model that can serve as a starting point for your own exploration of diffusion models for your applications.
This one-hour course, instructed by the creator of LangChain Harrison Chase as well as Andrew Ng will vastly expand the possibilities for leveraging powerful language models, where you can now create incredibly robust applications in a matter of hours.
Register for this course and see more details by visiting:
OpenCourser.com/course/8lvjo3/langchain
What's inside
Syllabus
Project Overview
In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.In this course you will learn and get experience with the following topics:1. Models, Prompts and Parsers: calling LLMs, providing prompts and parsing the response.2. Memories for LLMs: memories to store conversations and manage limited context space.3. Chains: creating sequences of operations.4. Question Answering over Documents: apply LLMs to your proprietary data and use case requirements.5. Agents: explore the powerful emerging development of LLM as reasoning agents.At the end of the course, you will have a model that can serve as a starting point for your own exploration of diffusion models for your applications.This one-hour course, instructed by the creator of LangChain Harrison Chase as well as Andrew Ng will vastly expand the possibilities for leveraging powerful language models, where you can now create incredibly robust applications in a matter of hours.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces LangChain, a less known framework for programming applications using language models, which is useful for practitioners in its field
Taught by Andrew Ng, an industry leader in artificial intelligence and deep learning
Suitable for learners who are familiar with language models and their capabilities and who seek to apply them in application development
Covers a range of topics, from fundamental language model usage to advanced concepts such as question answering and agent design
Practical in nature, with a focus on building a working model by the end of the course
May require additional learning for those new to natural language processing or language model applications
Save this course
Save LangChain for LLM Application Development 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 LangChain for LLM Application Development with these
activities:
Review Concepts from Intro to Computer Science
Show steps
Review the basics of computer science, such as data structures, algorithms, and programming paradigms.
Browse courses on
Programming Fundamentals
Show steps
-
Review lecture notes and textbooks from previous Intro to Computer Science course.
-
Complete practice problems and exercises.
-
Attend office hours or meet with a tutor for assistance.
Review core programming concepts
Show steps
Refreshing your programming skills will provide a solid foundation for understanding the technical aspects of LLM application development.
Browse courses on
Programming Concepts
Show steps
-
Go through tutorials or online courses that cover core programming concepts.
-
Solve coding problems and exercises to practice applying these concepts.
-
Review documentation or reference materials to reinforce your understanding.
Review diffusion models
Show steps
By reviewing diffusion models, you will be able to strengthen your understanding of the foundations of the course and be better prepared to dive deeper into the course material.
Browse courses on
Language Models
Show steps
-
Read through lecture notes or textbooks on diffusion models.
-
Summarize the key concepts of diffusion models, focusing on their strengths and weaknesses.
-
Complete practice problems or exercises to test your understanding of diffusion models.
13 other activities
Expand to see all activities and additional details
Show all 16 activities
Practice using the LangChain framework through online coding challenges
Show steps
Regular practice will help you develop a deeper understanding of the LangChain framework and its applications, improving your ability to build robust LLM-based applications.
Browse courses on
LangChain
Show steps
-
Identify online coding challenges that focus on LangChain and LLM application development.
-
Attempt the challenges, experimenting with different approaches and optimizing your solutions.
-
Review and analyze your submissions, identifying areas for improvement.
Complete Coding Challenges on LeetCode
Show steps
Practice solving coding challenges to improve your problem-solving and coding skills.
Show steps
-
Choose a set of coding challenges related to LangChain.
-
Attempt to solve the challenges on your own.
-
Review solutions and discuss with peers or mentors.
Participate in Study Groups or Q&A Forums
Show steps
Engage with peers to discuss course topics, ask questions, and share knowledge.
Show steps
-
Join online study groups or forums related to LangChain.
-
Actively participate in discussions and ask questions.
-
Contribute your knowledge and insights to help others.
Read 'Deep Learning' by Ian Goodfellow, Yoshua Bengio, Aaron Courville
Show steps
This book provides a comprehensive overview of deep learning principles and techniques, helping you build a solid foundation and enhance your understanding of LLM application development.
View
Deep Learning
on Amazon
Show steps
-
Read each chapter thoroughly, taking notes on key concepts and examples.
-
Complete the exercises and practice problems to reinforce your understanding.
-
Discuss the book's content with classmates or colleagues to exchange insights.
Follow Tutorials on LangChain Framework
Show steps
Learn about the LangChain framework and its applications through guided tutorials.
Show steps
-
Identify a specific aspect of LangChain you want to learn more about.
-
Find and follow online tutorials or documentation on the topic.
-
Complete the exercises and examples provided in the tutorials.
Practice applying prompts to language models
Show steps
To enhance your command of language models, this exercise will provide you hands-on experience in crafting effective prompts.
Browse courses on
AI Language Models
Show steps
-
Select a variety of different language models.
-
For each model, experiment with writing several unique prompts.
-
Analyze the responses generated by the models and identify patterns in their behavior.
Follow tutorials on LangChain framework
Show steps
Hands-on tutorials will guide you through practical applications of the LangChain framework, empowering you to build robust LLM-based applications.
Browse courses on
LangChain
Show steps
-
Identify tutorials that cover the specific aspects of LangChain you want to explore.
-
Follow the tutorials step-by-step, replicating the code and experimenting with different parameters.
-
Seek clarification or support from the tutorial providers or online communities if needed.
Join a study group or discussion forum on LLM application development
Show steps
Engaging with peers will provide opportunities to exchange knowledge, ask questions, and reinforce your understanding of the course content.
Show steps
-
Identify a study group or discussion forum that aligns with your interests.
-
Participate actively in discussions, sharing your insights and seeking clarification.
-
Collaborate on projects or assignments with other members of the group.
Explore advanced techniques for using LangChain
Show steps
To broaden your proficiency with LangChain, this activity will guide you through more sophisticated methods and techniques.
Show steps
-
Locate and review online tutorials or documentation on advanced LangChain techniques.
-
Follow the tutorials to implement these techniques in your own projects.
-
Experiment with different combinations of techniques to optimize your results.
Mentor Junior Developers or Students Learning LangChain
Show steps
Share your knowledge and expertise with others by mentoring junior developers or students.
Browse courses on
Mentoring
Show steps
-
Identify individuals who could benefit from your guidance.
-
Establish regular meetings or communication channels.
-
Provide guidance, support, and resources to help them learn and grow.
-
Share your experiences and insights from working with LangChain.
Attend a workshop on LLM applications
Show steps
Workshops offer immersive learning experiences, allowing you to delve deeper into specific aspects of LLM application development with guidance from experts.
Show steps
-
Research and identify workshops that align with your learning objectives.
-
Prepare for the workshop by reviewing relevant materials or completing pre-work assignments.
-
Attend the workshop and actively participate in discussions and exercises.
-
Apply the knowledge and skills gained from the workshop to your own projects or assignments.
Build a simple question answering system using a language model
Show steps
By undertaking this project, you will gain practical experience in applying language models to solve real-world problems.
Show steps
-
Gather a dataset of questions and answers.
-
Train a language model on the dataset.
-
Develop a user interface for your question answering system.
-
Test and evaluate your system's performance.
Contribute to LangChain Open-Source Projects
Show steps
Make meaningful contributions to the LangChain community by participating in open-source projects.
Browse courses on
Community Involvement
Show steps
-
Identify an open-source project related to LangChain.
-
Review the project's documentation and codebase.
-
Identify an area where you can contribute.
-
Submit a pull request with your proposed changes.
Review Concepts from Intro to Computer Science
Show steps
Review the basics of computer science, such as data structures, algorithms, and programming paradigms.
Browse courses on
Programming Fundamentals
Show steps
Show steps
Show steps
- Review lecture notes and textbooks from previous Intro to Computer Science course.
- Complete practice problems and exercises.
- Attend office hours or meet with a tutor for assistance.
Review core programming concepts
Show steps
Refreshing your programming skills will provide a solid foundation for understanding the technical aspects of LLM application development.
Browse courses on
Programming Concepts
Show steps
Show steps
Show steps
- Go through tutorials or online courses that cover core programming concepts.
- Solve coding problems and exercises to practice applying these concepts.
- Review documentation or reference materials to reinforce your understanding.
Review diffusion models
Show steps
By reviewing diffusion models, you will be able to strengthen your understanding of the foundations of the course and be better prepared to dive deeper into the course material.
Browse courses on
Language Models
Show steps
Show steps
Show steps
- Read through lecture notes or textbooks on diffusion models.
- Summarize the key concepts of diffusion models, focusing on their strengths and weaknesses.
- Complete practice problems or exercises to test your understanding of diffusion models.
13 other activities
Expand to see all activities and additional details
Show all 16 activities
Practice using the LangChain framework through online coding challenges
Show steps
Regular practice will help you develop a deeper understanding of the LangChain framework and its applications, improving your ability to build robust LLM-based applications.
Browse courses on
LangChain
Show steps
Show steps
Show steps
- Identify online coding challenges that focus on LangChain and LLM application development.
- Attempt the challenges, experimenting with different approaches and optimizing your solutions.
- Review and analyze your submissions, identifying areas for improvement.
Complete Coding Challenges on LeetCode
Show steps
Practice solving coding challenges to improve your problem-solving and coding skills.
Show steps
Show steps
Show steps
- Choose a set of coding challenges related to LangChain.
- Attempt to solve the challenges on your own.
- Review solutions and discuss with peers or mentors.
Participate in Study Groups or Q&A Forums
Show steps
Engage with peers to discuss course topics, ask questions, and share knowledge.
Show steps
Show steps
Show steps
- Join online study groups or forums related to LangChain.
- Actively participate in discussions and ask questions.
- Contribute your knowledge and insights to help others.
Read 'Deep Learning' by Ian Goodfellow, Yoshua Bengio, Aaron Courville
Show steps
This book provides a comprehensive overview of deep learning principles and techniques, helping you build a solid foundation and enhance your understanding of LLM application development.
View
Deep Learning
on Amazon
Show steps
Show steps
Show steps
- Read each chapter thoroughly, taking notes on key concepts and examples.
- Complete the exercises and practice problems to reinforce your understanding.
- Discuss the book's content with classmates or colleagues to exchange insights.
Follow Tutorials on LangChain Framework
Show steps
Learn about the LangChain framework and its applications through guided tutorials.
Show steps
Show steps
Show steps
- Identify a specific aspect of LangChain you want to learn more about.
- Find and follow online tutorials or documentation on the topic.
- Complete the exercises and examples provided in the tutorials.
Practice applying prompts to language models
Show steps
To enhance your command of language models, this exercise will provide you hands-on experience in crafting effective prompts.
Browse courses on
AI Language Models
Show steps
Show steps
Show steps
- Select a variety of different language models.
- For each model, experiment with writing several unique prompts.
- Analyze the responses generated by the models and identify patterns in their behavior.
Follow tutorials on LangChain framework
Show steps
Hands-on tutorials will guide you through practical applications of the LangChain framework, empowering you to build robust LLM-based applications.
Browse courses on
LangChain
Show steps
Show steps
Show steps
- Identify tutorials that cover the specific aspects of LangChain you want to explore.
- Follow the tutorials step-by-step, replicating the code and experimenting with different parameters.
- Seek clarification or support from the tutorial providers or online communities if needed.
Join a study group or discussion forum on LLM application development
Show steps
Engaging with peers will provide opportunities to exchange knowledge, ask questions, and reinforce your understanding of the course content.
Show steps
Show steps
Show steps
- Identify a study group or discussion forum that aligns with your interests.
- Participate actively in discussions, sharing your insights and seeking clarification.
- Collaborate on projects or assignments with other members of the group.
Explore advanced techniques for using LangChain
Show steps
To broaden your proficiency with LangChain, this activity will guide you through more sophisticated methods and techniques.
Show steps
Show steps
Show steps
- Locate and review online tutorials or documentation on advanced LangChain techniques.
- Follow the tutorials to implement these techniques in your own projects.
- Experiment with different combinations of techniques to optimize your results.
Mentor Junior Developers or Students Learning LangChain
Show steps
Share your knowledge and expertise with others by mentoring junior developers or students.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Identify individuals who could benefit from your guidance.
- Establish regular meetings or communication channels.
- Provide guidance, support, and resources to help them learn and grow.
- Share your experiences and insights from working with LangChain.
Attend a workshop on LLM applications
Show steps
Workshops offer immersive learning experiences, allowing you to delve deeper into specific aspects of LLM application development with guidance from experts.
Show steps
Show steps
Show steps
- Research and identify workshops that align with your learning objectives.
- Prepare for the workshop by reviewing relevant materials or completing pre-work assignments.
- Attend the workshop and actively participate in discussions and exercises.
- Apply the knowledge and skills gained from the workshop to your own projects or assignments.
Build a simple question answering system using a language model
Show steps
By undertaking this project, you will gain practical experience in applying language models to solve real-world problems.
Show steps
Show steps
Show steps
- Gather a dataset of questions and answers.
- Train a language model on the dataset.
- Develop a user interface for your question answering system.
- Test and evaluate your system's performance.
Contribute to LangChain Open-Source Projects
Show steps
Make meaningful contributions to the LangChain community by participating in open-source projects.
Browse courses on
Community Involvement
Show steps
Show steps
Show steps
- Identify an open-source project related to LangChain.
- Review the project's documentation and codebase.
- Identify an area where you can contribute.
- Submit a pull request with your proposed changes.
Career center
Learners who complete LangChain for LLM Application Development will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/8lvjo3/langchain
Reading list
We haven't picked any books for this reading list yet.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8lvjo3/langchain
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Effort
1 hour
Level
Introductory
Via
Coursera
Institution
DeepLearning.AI
Instructors
Harrison Chase
Andrew Ng
Session
August 26, 2024
- September 9, 2024
Language
English
Good to know
Introduces LangChain, a less known framework for programming applications using language models, which is useful for practitioners in its field
Taught by Andrew Ng, an industry leader in artificial intelligence and deep learning
Suitable for learners who are familiar with language models and their capabilities and who seek to apply them in application development
Covers a range of topics, from fundamental language model usage to advanced concepts such as question answering and agent design
Practical in nature, with a focus on building a working model by the end of the course
May require additional learning for those new to natural language processing or language model applications
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