DADataCamp
Developing LLM Applications with LangChain
Intermediate 3 hours English Completion Certificate
What you'll learn
Build LLM applications with the LangChain framework
Compose chains that combine prompts and models
Implement retrieval-augmented generation (RAG)
Create agents that can call tools and take actions
Work with both OpenAI and Hugging Face models
Develop a chatbot backed by your own documents
This course includes
3h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
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Prices & availability can change — confirm on the provider's site. We're not affiliated with any single provider.
Instructor
JB
Jonathan Bennion
DataCamp instructor
— learners— courses — instructor rating
Taught by Jonathan Bennion, an AI engineer and LangChain contributor, with a practical, production-minded perspective on building LLM apps.
Requirements
- Intermediate Python
- Familiarity with calling an LLM API
Who this course is for
- Developers building LLM-powered apps
- Python users moving beyond basic API calls
- Engineers prototyping RAG and agents
About this provider
DA
DataCamp
Data science and analytics learning platform. 10M+ learners, hands-on coding exercises.
4.4 trust score
Frequently asked questions
LLM-powered apps using LangChain — including retrieval (RAG) systems that answer from your own data and agents that can use tools — across OpenAI and Hugging Face.
No — it's intermediate. You'll want comfortable Python and some experience calling an LLM API (e.g. via Working with the OpenAI API) first.
A popular open-source framework that makes it easier to combine LLMs with prompts, data retrieval, memory, and tools to build real applications.
About three hours of hands-on building.
Included with a DataCamp subscription (~$29/month annually). Note that running LLM apps you build will also use the model provider's own API pricing.