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 Stuttgart can be carried out locally on customer premises or in NobleProg corporate training centers.
Our training facilities are located at Löffelstraße 40 in Stuttgart. Our spacious tr...
Overview
Our training facilities are located at Löffelstraße 40 in Stuttgart. Our spacious training rooms are easy to reach thanks to good traffic connections and offer optimal training conditions.
Arrival
The NobleProg training facilities are conveniently located near the B27, the feeder road to the A8 motorway. If you arrive by public transport, the nearest underground station is Degerloch/Albstrasse.
Parking
Around our training rooms you will find numerous parking spaces which are not subject to charges.
Local Services
Not far from Löfflerstrasse you will find various restaurants and hotels, including the Hotel Harambe Afrika.
This instructor-led, live training in Stuttgart (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 Stuttgart (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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