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 training can be carried out locally on customer premises in Salzburg or in NobleProg corporate training centers in Salzburg.
Our training facilities are located atAdolf-Kolping-Str. 10 in Salzburg. Our spacious ...
Overview
Our training facilities are located atAdolf-Kolping-Str. 10 in Salzburg. Our spacious training rooms are located near the Salzach river, within walking distance of the old town, and offer optimal training conditions for your needs.
Arrival
The NobleProg training facilities are conveniently located near the A1 motorway and the train station and Europark Salzburg Taxham train station are easily accessible.
Parking
Parking is available in the surrounding streets around our training rooms.
Local Services
In the area of the city centre there are numerous restaurants and also hotels are within walking distance.
This instructor-led, live training in Salzburg (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 Salzburg (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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