Learn how to enrich data analytics with GenAI without writing a line of code.
During this event, we will explore a fraud detection use case and we will exploit the multi-language capabilities of GenAI to automatically generate custom alert messages.
During this hands-on workshop you will get familiar with the free low-code tool KNIME Analytics Platform, techniques for fraud detection, and the use of GenAI via the KNIME AI Extension (Labs).
Completely new to KNIME? We’ve got you covered! We will start with an introduction to KNIME Analytics Platform, making it easy to follow along even for newbies!
Without any coding experience you will learn to:
- Detect frauds in investment contracts visually and using statistical techniques
- Prompt engineer an LLM via the OpenAI integration
- Create a vector store from a corpus of different types of investment contracts (the knowledge base)
- Build and deploy a data app to display email alerts and make it available to authenticated users on a web browser
Other KNIME AI integrations we will discuss include GPT4All, Hugging Face, Chroma, FAISS and more.
Please come prepared and bring your laptop with KNIME Analytics Platform and the KNIME AI Extension (Labs) already installed.
Please note if you want to join onsite, registration is mandatory.
Agenda:
6:00 PM – Doors open, Welcome
6:10 PM – 6:40 PM : Introduction to KNIME, Demo of KNIME Analytics Platform and Q&A
6:40 PM – 7:10 PM : Introduction to fraud detection techniques, LLMs and the KNIME AI Extension (Labs) and Q&A
7:10 PM – 8:30 PM : Enrich Data Analytics for Fraud Detection with GenAI. We’ll open KNIME on our laptops and build a KNIME workflow!
8:30 PM – 9:00 PM : Networking and refreshments
Meet the speakers:
Schalk Gerber : Schalk leads the Education team at KNIME. As a certified instructional designer, he is involved in various aspects of course design, content creation, and certification. With more than 10 years of experience in teaching business ethics and facilitating difficult discussions on topics like sustainability, inequality, and ethical leadership, he now focuses on helping people learn how to make sense of their data with analytics and AI. He holds a PhD in philosophy on ethics.
Linus Krause: Linus has a mixed background in both psychology and computer science. During his bachelor’s degree in psychology in Hamburg, he worked as a research assistant in various fields and as a tutor for statistics. To bridge the gap between “Social Sciences” and “Computer Science”, he additionally studied Computer Science (BA) for one year. He is currently studying “Social and Economic Data Science” (MA) in Konstanz with a focus on Natural Language Processing (NLP) and Large Language Models (LLMs). Linus is now working as a student trainee at KNIME. He started out analyzing competitors and has since switched to the education team, where he creates teaching materials and also teaches KNIME himself.
