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 Słupsk can be carried out locally on customer premises or in NobleProg corporate training centers.
The training room is located just 3 kilometers from the city center. It is a convenient location that allows easy access for ...
The training room is located just 3 kilometers from the city center. It is a convenient location that allows easy access for both city residents and those coming from outside. For those traveling by train, the Słupsk Północny train station is just 450 meters away from the facility. For those preferring to travel by bus, there is a bus stop right in front of the facility. The entire room's equipment has been carefully selected to provide functionality, comfort, and an atmosphere conducive to the development of various training sessions.
This instructor-led, live training in Słupsk (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 Słupsk (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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