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Build LLM Apps with LangChain.js
Jacob Lee
Jacob Lee
JavaScript is the world’s most popular programming language, and now developers can program in JavaScript to build powerful LLM apps.
Read more
JavaScript is the world’s most popular programming language, and now developers can program in JavaScript to build powerful LLM apps.
Read more
JavaScript is the world’s most popular programming language, and now developers can program in JavaScript to build powerful LLM apps.
This course will show webdevs how to expand their toolkits with LangChain.js, a popular JavaScript framework for building with LLMs, and will cover useful concepts for creating powerful, context-aware applications.
Register for this course and see more details by visiting:
OpenCourser.com/course/sbpv71/build
What's inside
Syllabus
Project Overview
JavaScript is the world’s most popular programming language, and now developers can program in JavaScript to build powerful LLM apps.This course will show webdevs how to expand their toolkits with LangChain.js, a popular JavaScript framework for building with LLMs, and will cover useful concepts for creating powerful, context-aware applications.By taking this course, you will: (1) Learn to use LangChain’s underlying abstractions to build your own JavaScript apps. (2) Understand the basics of retrieval augmented generation (RAG). (3) Have the structure of a basic conversational retrieval system that you can use for building your own chatbots.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Strong fit for web developers seeking to expand their skillset with JavaScript-based LLM applications
Emphasizes the basics of retrieval augmented generation (RAG), a core concept in natural language processing
Facilitates the development of conversational retrieval systems, highly relevant for building chatbots and other interactive applications
Teaches the fundamentals of LangChain.js, a popular JavaScript framework specifically designed for LLM development
Builds on the learner's existing JavaScript skills
Requires learners to have a basic understanding of programming concepts
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Activities
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Build LLM Apps with LangChain.js.
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Career center
Learners who complete Build LLM Apps with LangChain.js will develop knowledge and skills
that may be useful to these careers:
Full-Stack Developer
Full-Stack Developer
Full Stack Developers are responsible for developing both the front end and back end of websites and applications. They have a strong understanding of both front end and back end technologies. This course can help Full Stack Developers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their applications. This knowledge can be used to create more powerful and context-aware applications.
Conversational AI Engineer
Conversational AI Engineer
Conversational AI Engineers are responsible for developing and deploying conversational AI models. They use programming languages such as Python, R, and Java to create models that can engage in natural language conversations with humans. This course can help Conversational AI Engineers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their models. This knowledge can be used to create more powerful and engaging conversational AI models.
Front-End Developer
Front-End Developer
Front End Developers are responsible for developing the user interface (UI) of websites and applications. They use programming languages such as HTML, CSS, and JavaScript to create visually appealing and functional designs. This course can help Front End Developers expand their skill set by teaching them how to use LangChain.js, a JavaScript framework for building with LLMs. This knowledge can be used to create more powerful and context-aware web applications.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing (NLP) Engineers are responsible for developing and deploying NLP models. They use programming languages such as Python, R, and Java to create models that can understand and generate human language. This course can help NLP Engineers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their models. This knowledge can be used to create more powerful and accurate NLP models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and deploying machine learning models. They use programming languages such as Python, R, and Java to create models that can learn from data and make predictions. This course can help Machine Learning Engineers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their models. This knowledge can be used to create more powerful and accurate machine learning models.
User Experience Designer (UX Designer)
User Experience Designer (UX Designer)
User Experience Designers (UX Designers) are responsible for designing the user interface (UI) of websites and applications. They work with front end developers to ensure that UI is visually appealing and easy to use. This course can help UX Designers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their designs. This knowledge can be used to create more user-friendly and intuitive interfaces.
Speech Recognition Engineer
Speech Recognition Engineer
Speech Recognition Engineers are responsible for developing and deploying speech recognition models. They use programming languages such as Python, R, and Java to create models that can recognize human speech. This course can help Speech Recognition Engineers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their models. This knowledge can be used to create more powerful and accurate speech recognition models.
Back-End Developer
Back-End Developer
Back End Developers are responsible for developing the server-side of websites and applications. They use programming languages such as Python, Java, and C# to create the logic and functionality of applications. This course can help Back End Developers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their applications. This knowledge can be used to create more intelligent and personalized applications.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are satisfied with their products and services. They work with customers to resolve issues, provide training, and build relationships. This course can help Customer Success Managers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their customer support. This knowledge can be used to create more efficient and effective customer support.
Sales Manager
Sales Manager
Sales Managers are responsible for leading and managing sales teams. They work with customers to identify their needs and develop sales strategies. This course can help Sales Managers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their sales process. This knowledge can be used to create more effective and personalized sales pitches.
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data. They use statistical and machine learning techniques to extract insights from data. This course can help Data Scientists expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their analysis. This knowledge can be used to create more powerful and accurate data analysis models.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. They work with engineers, designers, and marketers to ensure that products meet the needs of customers. This course can help Product Managers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their products. This knowledge can be used to create more innovative and user-friendly products.
Technical Writer
Technical Writer
Technical Writers are responsible for creating documentation for software and other technical products. They work with engineers and product managers to ensure that documentation is accurate and easy to understand. This course can help Technical Writers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their documentation. This knowledge can be used to create more comprehensive and engaging documentation.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. They work with product managers, sales teams, and customers to ensure that products reach their target audience. This course can help Marketing Managers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their marketing campaigns. This knowledge can be used to create more effective and targeted marketing campaigns.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers are responsible for developing and deploying computer vision models. They use programming languages such as Python, R, and Java to create models that can analyze and interpret images. This course can help Computer Vision Engineers expand their skill set by teaching them how to use LangChain.js to integrate LLMs into their models. This knowledge can be used to create more powerful and accurate computer vision models.
For more career information including salaries, visit:
OpenCourser.com/course/sbpv71/build
Reading list
We've selected ten 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
Build LLM Apps with LangChain.js.
This classic textbook provides a comprehensive overview of speech and language processing, covering topics such as phonetics, phonology, morphology, syntax, semantics, and pragmatics. It valuable resource for anyone who wants to learn more about the fundamentals of human language.
Save
Comprehensive introduction to deep learning, a type of machine learning that has achieved state-of-the-art results on a wide range of tasks, including image recognition, natural language processing, and speech recognition. It covers the fundamentals of deep learning, including neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive overview of statistical learning, a subfield of machine learning that deals with the analysis of data. It covers topics such as linear regression, logistic regression, and support vector machines.
Provides a comprehensive overview of pattern recognition and machine learning, covering topics such as Bayesian inference, neural networks, and support vector machines. It valuable resource for anyone who wants to learn more about the theoretical foundations of machine learning.
Provides a comprehensive overview of information theory, inference, and learning algorithms, covering topics such as entropy, mutual information, and Bayesian inference. It valuable resource for anyone who wants to learn more about the theoretical foundations of machine learning.
Provides a comprehensive overview of machine learning from a probabilistic perspective, covering topics such as Bayesian inference, graphical models, and reinforcement learning. It valuable resource for anyone who wants to learn more about the theoretical foundations of machine learning.
Provides a practical guide to deep learning with Python, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone who wants to learn more about the practical aspects of deep learning.
Provides a practical guide to natural language processing with Python, covering topics such as tokenization, stemming, and lemmatization, as well as advanced topics such as language modeling, machine translation, and question answering. It valuable resource for anyone who wants to learn more about the practical aspects of natural language processing.
Provides a practical guide to speech and language processing with Python, covering topics such as phonetics, phonology, morphology, syntax, semantics, and pragmatics. It valuable resource for anyone who wants to learn more about the practical aspects of speech and language processing.
Provides a comprehensive overview of deep learning for natural language processing, covering topics such as word embeddings, attention mechanisms, and transformer networks. It valuable resource for anyone who wants to learn more about the theoretical foundations of deep learning for natural language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/sbpv71/build
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Effort
2
Level
Intermediate
Via
Coursera
Institution
DeepLearning.AI
Instructor
Jacob Lee
Language
English
Good to know
Strong fit for web developers seeking to expand their skillset with JavaScript-based LLM applications
Emphasizes the basics of retrieval augmented generation (RAG), a core concept in natural language processing
Facilitates the development of conversational retrieval systems, highly relevant for building chatbots and other interactive applications
Teaches the fundamentals of LangChain.js, a popular JavaScript framework specifically designed for LLM development
Builds on the learner's existing JavaScript skills
Requires learners to have a basic understanding of programming concepts
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