In this hands-on workshop we take a look behind the buzzwords: Machine Learning & Data Science.
🎓 What will you learn?
- The difference between AI and ML
- The different types of Machine Learning
- How to structure Data Science projects
We will develop a Machine Learning model to predict customer churn with an AutoAI feature – to build Machine Learning models automatically – as well as Jupyter Notebooks. For this hands-on session we will be using the Cloud Pak for Data as a Service on the IBM Cloud.
🤖 Learn Automation, Data & AI and develop your own app!
Interested in Machine Learning and Data Science? Discover automation like you’ve never seen it before: in customer service, the AI lifecycle, document processing and classification, application monitoring for cloud-native applications, and Robotic Process Automation! Register for free and get ready to learn about all these amazing technologies with live-demos in this series of virtual events. Get hands-on and build your own app afterwards.
👍 What’s the benefit for you?
In the last session of this event series you will have the opportunity to bring your own use case / problem / data / application / processes / documents / … and pitch it in 10 – 15 minutes to our IBM technical staff. They will give you feedback, provide technical support, and perhaps even become part of your project!
– Felix Augenstein, Data Scientist, IBM
Felix Augenstein is a Data Scientist at IBM and part of the Hybrid Cloud Build Team in the DACH market. His focus is on technologies like IBM Watson, Data & AI, as well as Automation. On these topics he enables independent software vendors (ISVs), system integrators (SIs), business partners, and other stakeholders in the ecosystem. He also supports them in the project-based integration of these technologies into their own products. Additionally, Felix creates content and tutorials for the developer community, which are then distributed through digital channels.
– Marion Nehring, Client & Ecosystem Lead, Program Manager, IBM