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. Maastricht onsite live LangChain trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
The meeting rooms at Stationsplein in Maastricht are located in an inspiring high building with large windows to enjoy the vi...
The meeting rooms at Stationsplein in Maastricht are located in an inspiring high building with large windows to enjoy the view over this international city. Outside spraying fountains that provide a soothing environment to work. A number of national and international service companies have established themselves in this part of the Netherlands, and in the city there are also many large companies, including specialists in logistics, IT, medical and veterinary technologies and life sciences. There are also a number of large call centers here. Many important Dutch and European government offices are located in the city.
This instructor-led, live training in Maastricht (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 Maastricht (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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