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. Bremen onsite live LangChain trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
Our training facilities are located at Konsul-Smidt-Str. 8 in Bremen. Our spacious tra...
Overview
Our training facilities are located at Konsul-Smidt-Str. 8 in Bremen. Our spacious training rooms are located near the Weser river, within walking distance of the European port, and offer optimal training conditions for your needs.
Arrival
The NobleProg training facilities are conveniently located near the Konsul-Smidt-Strasse stop, Bremen main station is easy to reach and Bremen can best be reached by car via the A1 motorway.
Parking
Parking is available in the surrounding streets around our training rooms.
Local Services
In the area of the Weser bank there are numerous restaurants and the city centre is within walking distance.
This instructor-led, live training in Bremen (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 Bremen (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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