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Tom Taulli
This is an intermediate-level course about LangChain. This course will teach you how to create generative AI applications using this powerful open source platform.
Read more
This is an intermediate-level course about LangChain. This course will teach you how to create generative AI applications using this powerful open source platform.
Read more
This is an intermediate-level course about LangChain. This course will teach you how to create generative AI applications using this powerful open source platform.
Although large-language models have become a must have offering for every company, they are still complex to develop and apply. In this course, LangChain Development, you’ll gain the ability to understand how to use the powerful LangChain framework to create real-world LLM (large-language model) applications. First, you’ll explore the fundamentals of this versatile system, including the use of generative AI models, prompt engineering and training. Next, you’ll discover how to make sophisticated applications that use memory, chains and agents. Finally, you’ll learn about how to use vector databases like Pinecone to access external documents, which will allow for richer programs. When you’re finished with this course, you’ll have the skills and knowledge of LangChain needed to understand their practical applications.
Register for this course and see more details by visiting:
OpenCourser.com/course/iz80hn/langchain
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What's inside
Syllabus
Course Overview
Understanding LangChain
Using Generative AI Models
Creating Prompts
Read more
Syllabus
Course Overview
Understanding LangChain
Using Generative AI Models
Creating Prompts
Read more
Learning about Memory
Deciphering Chains
Building Agents
Exploring Indexes and Vector Databases
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by Tom Taulli, an expert on LangChain and AI who is highly reputable
Suitable for intermediate-level learners or those with some prior knowledge of LangChain
Covers a wide range of advanced topics, including using memory, chains, and agents
Suitable for those interested in creating real-world LLM applications
Provides hands-on experience in building generative AI applications
Requires access to external resources such as Pinecone vector databases
Save this course
Save LangChain Development to your list so you can find it easily later:
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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 Development with these
activities:
Review Prompt Engineering
Show steps
Revising fundamental concepts of prompt engineering will equip you to write effective prompts, maximizing LLM capabilities.
Browse courses on
Prompt Engineering
Show steps
-
Study online resources on prompt engineering.
-
Practice writing prompts for various use cases.
Review NLP fundamentals
Show steps
Ensure a strong foundation for understanding LangChain by reviewing key concepts in Natural Language Processing.
Browse courses on
NLP
Show steps
-
Revisit the course materials on NLP from your previous coursework.
-
Read a chapter or two from a textbook on NLP.
-
Watch a few online tutorials on NLP basics.
Attend Study Group
Show steps
Engaging in peer study sessions will provide a supportive environment for knowledge exchange, problem-solving, and reinforcing concepts.
Show steps
-
Find or create a study group with fellow LangChain learners.
-
Establish regular meeting times and set clear goals for each session.
-
Take turns presenting topics, leading discussions, and facilitating activities.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Work through the LangChain documentation
Show steps
Familiarize yourself with the basics of LangChain and its capabilities through the provided documentation.
Browse courses on
LangChain
Show steps
-
Explore the LangChain website and read through the introductory materials.
-
Set up a LangChain account and follow the onboarding instructions.
-
Review the LangChain API documentation and identify key functions.
-
Complete the sample tutorials provided by LangChain.
Explore Vector Databases
Show steps
Delving into tutorials on vector databases will enhance your understanding of how to effectively access and utilize external documents, leading to richer applications.
Browse courses on
Vector Databases
Show steps
-
Identify reputable online tutorials on vector databases.
-
Follow the tutorials, taking notes and experimenting with code examples.
-
Apply your newfound knowledge to your LangChain projects.
Practice Using the Generative AI Models
Show steps
Build strong foundational skills by practicing the use of AI models
Browse courses on
Generative AI Models
Show steps
-
Follow along with the course exercises using a sandbox or local environment.
-
Experiment with different model parameters and settings.
-
Create your own custom prompts and evaluate the results.
Generate prompts for various tasks
Show steps
Fine-tune your prompt engineering skills by practicing how to craft effective prompts for different AI tasks.
Browse courses on
Prompt Engineering
Show steps
-
Identify a specific task you want to perform using an LLM.
-
Brainstorm a list of keywords and phrases related to the task.
-
Experiment with different prompt formats and structures.
-
Test your prompts with LangChain and iterate based on the results.
Develop a Simple LLM Application
Show steps
Apply your knowledge to create a real-world application using LLM
Show steps
-
Choose a specific use case for your application.
-
Design the architecture and workflow of your application.
-
Implement your application using LangChain.
-
Test and refine your application to ensure it meets your requirements.
Create a short video tutorial
Show steps
Craft a video that teaches viewers how to build a simple LLM application using LangChain.
Browse courses on
Generative AI Applications
Show steps
-
Choose a specific AI application to build.
-
Sketch out the workflow of your application.
-
Code your application.
-
Record your screen while demonstrating the functionality of your application.
-
Add a voiceover to your video, explaining your thought process.
Create Generative AI Applications
Show steps
Through consistent practice, you'll develop proficiency in designing and building real-world applications leveraging generative AI.
Browse courses on
Generative AI Applications
Show steps
-
Identify a problem or task suitable for a generative AI solution.
-
Design the application's architecture and workflow.
-
Implement the application using LangChain.
-
Evaluate the application's performance and fine-tune it for optimal results.
Build a chatbot using LangChain
Show steps
Apply your knowledge of LangChain by creating a functional chatbot that can interact with users.
Browse courses on
LangChain
Show steps
-
Design the conversation flow and user interface for your chatbot.
-
Create a LangChain model for your chatbot's responses.
-
Integrate the LangChain model with your chatbot's interface.
-
Test your chatbot's functionality and make improvements as needed.
Write a Blog Post or Article
Show steps
Documenting your learning journey through blog posts or articles will deepen your understanding, enhance your writing skills, and potentially benefit others.
Show steps
-
Choose a specific topic or aspect of LangChain to cover.
-
Conduct research and gather relevant information.
-
Outline your article, organizing your thoughts and ideas.
-
Write the article, ensuring clarity, conciseness, and proper grammar.
-
Edit and proofread your article carefully before publishing it.
Build a Memory-Based Application
Show steps
Hands-on experience in building applications that utilize memory capabilities will strengthen your understanding of LangChain's functionalities.
Browse courses on
Natural Language Processing
Show steps
-
Conceive an application idea that leverages memory for context-aware interactions.
-
Design the application's architecture, considering memory management and retrieval.
-
Implement the application using LangChain's memory features.
-
Test the application thoroughly, evaluating its ability to retain and retrieve information.
-
Refine the application based on testing results, optimizing performance and user experience.
Build a Complete Generative AI Application
Show steps
Embarking on a substantial project that encompasses the entire LangChain development process will solidify your skills and demonstrate your proficiency.
Browse courses on
Natural Language Processing
Show steps
-
Define the scope and objectives of your project.
-
Design and implement the application using LangChain.
-
Test and evaluate the application thoroughly.
-
Document your project, including its architecture, implementation details, and evaluation results.
-
Share your project with others, such as through a public repository or presentation.
Review Prompt Engineering
Show steps
Revising fundamental concepts of prompt engineering will equip you to write effective prompts, maximizing LLM capabilities.
Browse courses on
Prompt Engineering
Show steps
Show steps
Show steps
- Study online resources on prompt engineering.
- Practice writing prompts for various use cases.
Review NLP fundamentals
Show steps
Ensure a strong foundation for understanding LangChain by reviewing key concepts in Natural Language Processing.
Browse courses on
NLP
Show steps
Show steps
Show steps
- Revisit the course materials on NLP from your previous coursework.
- Read a chapter or two from a textbook on NLP.
- Watch a few online tutorials on NLP basics.
Attend Study Group
Show steps
Engaging in peer study sessions will provide a supportive environment for knowledge exchange, problem-solving, and reinforcing concepts.
Show steps
Show steps
Show steps
- Find or create a study group with fellow LangChain learners.
- Establish regular meeting times and set clear goals for each session.
- Take turns presenting topics, leading discussions, and facilitating activities.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Work through the LangChain documentation
Show steps
Familiarize yourself with the basics of LangChain and its capabilities through the provided documentation.
Browse courses on
LangChain
Show steps
Show steps
Show steps
- Explore the LangChain website and read through the introductory materials.
- Set up a LangChain account and follow the onboarding instructions.
- Review the LangChain API documentation and identify key functions.
- Complete the sample tutorials provided by LangChain.
Explore Vector Databases
Show steps
Delving into tutorials on vector databases will enhance your understanding of how to effectively access and utilize external documents, leading to richer applications.
Browse courses on
Vector Databases
Show steps
Show steps
Show steps
- Identify reputable online tutorials on vector databases.
- Follow the tutorials, taking notes and experimenting with code examples.
- Apply your newfound knowledge to your LangChain projects.
Practice Using the Generative AI Models
Show steps
Build strong foundational skills by practicing the use of AI models
Browse courses on
Generative AI Models
Show steps
Show steps
Show steps
- Follow along with the course exercises using a sandbox or local environment.
- Experiment with different model parameters and settings.
- Create your own custom prompts and evaluate the results.
Generate prompts for various tasks
Show steps
Fine-tune your prompt engineering skills by practicing how to craft effective prompts for different AI tasks.
Browse courses on
Prompt Engineering
Show steps
Show steps
Show steps
- Identify a specific task you want to perform using an LLM.
- Brainstorm a list of keywords and phrases related to the task.
- Experiment with different prompt formats and structures.
- Test your prompts with LangChain and iterate based on the results.
Develop a Simple LLM Application
Show steps
Apply your knowledge to create a real-world application using LLM
Show steps
Show steps
Show steps
- Choose a specific use case for your application.
- Design the architecture and workflow of your application.
- Implement your application using LangChain.
- Test and refine your application to ensure it meets your requirements.
Create a short video tutorial
Show steps
Craft a video that teaches viewers how to build a simple LLM application using LangChain.
Browse courses on
Generative AI Applications
Show steps
Show steps
Show steps
- Choose a specific AI application to build.
- Sketch out the workflow of your application.
- Code your application.
- Record your screen while demonstrating the functionality of your application.
- Add a voiceover to your video, explaining your thought process.
Create Generative AI Applications
Show steps
Through consistent practice, you'll develop proficiency in designing and building real-world applications leveraging generative AI.
Browse courses on
Generative AI Applications
Show steps
Show steps
Show steps
- Identify a problem or task suitable for a generative AI solution.
- Design the application's architecture and workflow.
- Implement the application using LangChain.
- Evaluate the application's performance and fine-tune it for optimal results.
Build a chatbot using LangChain
Show steps
Apply your knowledge of LangChain by creating a functional chatbot that can interact with users.
Browse courses on
LangChain
Show steps
Show steps
Show steps
- Design the conversation flow and user interface for your chatbot.
- Create a LangChain model for your chatbot's responses.
- Integrate the LangChain model with your chatbot's interface.
- Test your chatbot's functionality and make improvements as needed.
Write a Blog Post or Article
Show steps
Documenting your learning journey through blog posts or articles will deepen your understanding, enhance your writing skills, and potentially benefit others.
Show steps
Show steps
Show steps
- Choose a specific topic or aspect of LangChain to cover.
- Conduct research and gather relevant information.
- Outline your article, organizing your thoughts and ideas.
- Write the article, ensuring clarity, conciseness, and proper grammar.
- Edit and proofread your article carefully before publishing it.
Build a Memory-Based Application
Show steps
Hands-on experience in building applications that utilize memory capabilities will strengthen your understanding of LangChain's functionalities.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Conceive an application idea that leverages memory for context-aware interactions.
- Design the application's architecture, considering memory management and retrieval.
- Implement the application using LangChain's memory features.
- Test the application thoroughly, evaluating its ability to retain and retrieve information.
- Refine the application based on testing results, optimizing performance and user experience.
Build a Complete Generative AI Application
Show steps
Embarking on a substantial project that encompasses the entire LangChain development process will solidify your skills and demonstrate your proficiency.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Define the scope and objectives of your project.
- Design and implement the application using LangChain.
- Test and evaluate the application thoroughly.
- Document your project, including its architecture, implementation details, and evaluation results.
- Share your project with others, such as through a public repository or presentation.
Career center
Learners who complete LangChain Development will develop knowledge and skills
that may be useful to these careers:
Technical Writer
Technical Writer
A Technical Writer conveys complex technical information to a non-specialist audience. This course provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications. You can also use vector databases like Pinecone to access external documents, which will allow for richer programs.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course helps build a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Data Scientist
Data Scientist
A Data Scientist analyzes and interprets data to extract insights and develop predictive models. This course helps build a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs and develops machine learning models. This course may be useful for a Machine Learning Engineer because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer designs and develops natural language processing systems. This course may be useful for a Natural Language Processing Engineer because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
AI Engineer
AI Engineer
An AI Engineer designs and develops AI systems. This course may be useful for an AI Engineer because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Computational Linguist
Computational Linguist
A Computational Linguist analyzes and interprets natural language data. This course may be useful for a Computational Linguist because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
UX Designer
UX Designer
A UX Designer designs and develops user experiences. This course may be useful for a UX Designer because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Data Analyst
Data Analyst
A Data Analyst analyzes and interprets data to extract insights. This course may be useful for a Data Analyst because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Information Architect
Information Architect
An Information Architect designs and organizes information systems. This course may be useful for an Information Architect because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Back-End Developer
Back-End Developer
A Back-End Developer designs and develops the server-side of a website or application. This course may be useful for a Back-End Developer because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Front-End Developer
Front-End Developer
A Front-End Developer designs and develops the user interface of a website or application. This course may be useful for a Front-End Developer because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. This course may be useful for a Database Administrator because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Full-Stack Developer
Full-Stack Developer
A Full-Stack Developer designs and develops both the front-end and back-end of a website or application. This course may be useful for a Full-Stack Developer because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
Cloud Architect
Cloud Architect
A Cloud Architect designs and manages cloud computing systems. This course may be useful for a Cloud Architect because it provides a foundation in understanding how to create generative AI applications using the LangChain framework. As a result, you can learn how to use generative AI models, prompt engineering, and training to create sophisticated applications.
For more career information including salaries, visit:
OpenCourser.com/course/iz80hn/langchain
Reading list
We've selected 13 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 Development.
Comprehensive guide to statistical learning. It covers the foundational concepts of statistical learning, as well as advanced techniques such as supervised learning, unsupervised learning, and time series analysis.
Provides a comprehensive overview of the mathematics behind machine learning. It covers the foundational concepts of linear algebra, calculus, and probability theory.
Provides a comprehensive overview of language models. It covers topics such as model architecture, training, and evaluation.
Comprehensive guide to deep learning for natural language processing. It covers the foundational concepts of deep learning, as well as advanced techniques such as transformer models.
Save
This classic work of cognitive science explores the nature of human language and thought. It provides a deep dive into the relationship between language, thought, and reality, and is essential reading for anyone interested in the foundations of AI.
Save
Comprehensive guide to deep learning, the most powerful type of machine learning. It covers the fundamentals of deep learning, as well as advanced topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks.
This textbook provides a comprehensive overview of speech and language processing, covering topics such as speech recognition, natural language understanding, and natural language generation. It valuable resource for anyone interested in the foundations of AI.
Provides a comprehensive overview of deep learning for natural language processing. It covers topics such as model architecture, training, and evaluation.
Save
This textbook provides a comprehensive overview of computer vision, covering topics such as image formation, feature detection, object recognition, and image segmentation. It valuable resource for anyone interested in the foundations of AI.
Save
This science fiction film explores the ethical implications of artificial intelligence. It gripping thriller that will keep you on the edge of your seat.
Provides a basic overview of artificial intelligence. It good starting point for anyone who is new to the field.
Provides a basic overview of machine learning. It good starting point for anyone who is new to the field.
Provides a basic overview of Python for data analysis. It good starting point for anyone who is new to the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/iz80hn/langchain
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Time
175 hours
Level
Intermediate
Via
Pluralsight
Instructor
Tom Taulli
Language
English
Good to know
Taught by Tom Taulli, an expert on LangChain and AI who is highly reputable
Suitable for intermediate-level learners or those with some prior knowledge of LangChain
Covers a wide range of advanced topics, including using memory, chains, and agents
Suitable for those interested in creating real-world LLM applications
Provides hands-on experience in building generative AI applications
Requires access to external resources such as Pinecone vector databases
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