Online or onsite, instructor-led live LangChain training courses demonstrate through interactive hands-on practice how to build AI-powered applications using the LangChain framework.
LangChain training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live LangChain trainings in Wroclaw can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Wrocław
NobleProg , Ludwika Rydygiera 2a/22, Wroclaw, Poland, 50-249
Classroom is located in the city center (right next to HP Park Plaza), just 10 minutes walk from the market square.
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Classroom is located in the city center (right next to HP Park Plaza), just 10 minutes walk from the market square.
The entrance to the building is located from the Śrutowa street.
Check our offer to rent rooms and rent computer equipment!
Parking
Near the classroom, the number of free parking spaces is limited, there is no paid parking zone (along Rydygiera, Śrutowa and Henryka Brodatego, Bolesława Drobnera streets).
Public transport
The nearest tram stops: Dubois, Pomorska
The nearest bus stops: Dubois
This instructor-led, live training in Wroclaw (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the practical skills for building AI-powered applications.By the end of this training, participants will be able to:
Grasp the fundamental principles of LangChain.
Set up and configure the LangChain environment.
Understand the architecture and how LangChain interacts with large language models (LLMs).
This instructor-led, live training in Wroclaw (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build AI-powered applications using the LangChain framework.By the end of this training, participants will be able to:
Understand the fundamentals of LangChain and its components.
Integrate LangChain with large language models (LLMs) like GPT-4.
Build modular AI applications using LangChain.
Troubleshoot common issues in LangChain applications.
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