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. Antwerp onsite live LangChain trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Antwerp
Hotel NH Collection Antwerp Centre, Pelikaanstraat 84, 2018 Antwerpen, Belgium, Antwerp, Belgium, 2018
The hotel has a conference capacity for up to 110 attendees, with 6 dedicated, flexible spaces available. A range of smaller...
The hotel has a conference capacity for up to 110 attendees, with 6 dedicated, flexible spaces available. A range of smaller boardrooms and a larger conference room is available for large and small meetings. The facilities include up-to-date audio-visual equipment, with refreshments available to order and an events planner on site for assistance. Unusually for a city center hotel, the hotel offers parking in its own garage.
This instructor-led, live training in Antwerp (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 Antwerp (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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