New track teaches developers how to build and deploy AI applications using LangChain
DataCamp, the leading online learning platform for data and AI skills, announced a partnership with LangChain to launch a new AI Engineering with LangChain track, helping software developers build a complete skillset to launch real AI applications at scale.
“AI engineering skills are quickly moving past the stage of nice-to-have, to an urgent need for talent that can build systems that are reliable, testable, and ready for production,” said Jo Cornelissen, CEO at DataCamp.
As companies move from experimenting with AI to deploying systems in production, the skills required are changing. Developers now need to build, evaluate, and ship AI applications with speed. The new learning track teaches these skills using tools from LangChain, the framework for building applications with large language models (LLMs).
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Designed for software developers and data practitioners with Python experience, the curriculum covers application development, evaluation, retrieval-augmented generation, tool use, and agent-based systems.
DataCamp will deliver the track through its innovative AI-native experience. Learners build and refine AI systems with support from an AI Tutor that provides real-time feedback, making the learning process highly interactive and aligned with real-world workflows.
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“We’re excited to see LangSmith and LangChain’s frameworks at the core of DataCamp’s new curriculum. Their AI-native learning experience, built with LangSmith, LangGraph, and LangChain, brings a true “learn by building” approach to life. It’s a great example of applied learning, and we’re looking forward to seeing what students create next,” said Geoff Ladwig, Head of Education at LangChain.
“AI engineering skills are quickly moving past the stage of nice-to-have, to an urgent need for talent that can build systems that are reliable, testable, and ready for production,” said Jo Cornelissen, CEO at DataCamp. “By partnering with LangChain, we’re aligning our training with the real tools and workflows teams are actually using to build and ship AI systems today.”
