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 Graz can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
NobleProg Graz
Waagner-Biro-Strasse 47, Graz, Austria, 8020
Overview
Our training facilities are located at Waagner-Biro-Strasse 47 in Graz. Our spacious training rooms are located directly in the old town and offer optimal training conditions for your needs.
Directions
The NobleProg training facilities are best reached via the A9 motorway and the federal highway 67.
Parking spaces
There are parking spaces in the streets around our training rooms as well as the ContiPark multi-storey car park.
Local infrastructure
There are numerous restaurants in the downtown area and hotels are also within walking distance.
This instructor-led, live training in Graz (online or onsite) is aimed at advanced-level AI researchers and policy makers who wish to explore the ethical implications of AI development and learn how to apply ethical guidelines when building AI solutions with LangChain.
By the end of this training, participants will be able to:
Identify key ethical issues in AI development with LangChain.
Understand the impact of AI on society and decision-making processes.
Develop strategies for building fair and transparent AI systems.
Implement ethical AI guidelines into LangChain-based projects.
This instructor-led, live training in Graz (online or onsite) is aimed at intermediate-level web developers and UX designers who wish to leverage LangChain to create intuitive and user-friendly web applications.
By the end of this training, participants will be able to:
Understand the fundamental concepts of LangChain and its role in enhancing web user experience.
Implement LangChain in web apps to create dynamic and responsive interfaces.
Integrate APIs into web apps to improve interactivity and user engagement.
Optimize user experience using LangChain’s advanced customization features.
Analyze user behavior data to fine-tune web app performance and experience.
This instructor-led, live training in Graz (online or onsite) is aimed at beginner-level business analysts and automation engineers who wish to understand how to use LangChain and APIs for automating repetitive tasks and workflows.
By the end of this training, participants will be able to:
Understand the basics of API integration with LangChain.
Automate repetitive workflows using LangChain and Python.
Utilize LangChain to connect various APIs for efficient business processes.
Create and automate custom workflows using APIs and LangChain’s automation capabilities.
This instructor-led, live training in Graz (online or onsite) is aimed at intermediate-level data professionals who wish to use LangChain to enhance their data analysis and visualization capabilities.
By the end of this training, participants will be able to:
Automate data retrieval and cleaning using LangChain.
Conduct advanced data analysis using Python and LangChain.
Create visualizations with Matplotlib and other Python libraries integrated with LangChain.
Leverage LangChain for generating natural language insights from data analysis.
This instructor-led, live training in Graz (online or onsite) is aimed at advanced-level data engineers and DevOps professionals who wish to leverage LangChain's capabilities by integrating it with various cloud services.
By the end of this training, participants will be able to:
Integrate LangChain with major cloud platforms such as AWS, Azure, and Google Cloud.
Utilize cloud-based APIs and services to enhance LangChain-powered applications.
Scale and deploy conversational agents to the cloud for real-time interaction.
Implement monitoring and security best practices in cloud environments.
This instructor-led, live training in Graz (online or onsite) is aimed at intermediate-level professionals who wish to deepen their understanding of conversational agents and apply LangChain to real-world use cases.
By the end of this training, participants will be able to:
Understand the fundamentals of LangChain and its application in building conversational agents.
Develop and deploy conversational agents using LangChain.
Integrate conversational agents with APIs and external services.
Apply Natural Language Processing (NLP) techniques to improve the performance of conversational agents.
This instructor-led, live training in Graz (online or onsite) is aimed at developers and IT professionals of all skill levels who wish to automate tasks and processes using AI without writing extensive code.
By the end of this training, participants will be able to:
Design and implement complex workflows using n8n's visual programming interface.
Integrate AI capabilities into workflows using LangChain.
Build custom chatbots and virtual assistants for various use cases.
Perform advanced data analysis and processing with AI agents.
This instructor-led, live training in Graz (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 Graz (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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