Machine Learning Essentials & Workflows
Join us for a two-part online lecture series that covers the essentials of Machine Learning – from understanding key algorithms to walking through a full project using the Data Science Lifecycle.
Questions? Feel free to get in touch, we’re happy to help! Contact us
Both lectures will be hosted by Sonja Hänzelmann (Head of Data Science, AWI).
Machine Learning Fundamentals with Application Examples (Lecture 1)
Date: October 15th 2025, 9 - 12 a.m.
Language: English
Online via Zoom (Register here for Lecture 1)
Open to everyone, no registration limits
Content:
• Introduction to Machine Learning
• Supervised vs. Unsupervised Learning – key concepts and use cases
• Unsupervised Learning – Finding patterns in data (Clustering, Dimensionality Reduction)
• Supervised Learning – Prediction models (Classification, Regression)
Level: Beginner-friendly, perfect for anyone looking to better understand and apply ML methods.
Machine Learning Workflows: From Problem to Product, the Data Science Lifecycle (Lecture 2)
Date: October 22th 2025, 9 - 12 a.m.
Language: English
Online via Zoom (Register here for Lecture 2) Open to everyone, no registration limits
Content:
We’ll walk through the Data Science Lifecycle using illustrative examples:
• Business Understanding – Defining the problem and setting goals
• Data Understanding – Exploration and analysis
• Data Preparation – Data cleaning and feature engineering
• Modelling – Selecting and training ML models (building on Lecture 1)
• Evaluation – Quality control and model performance
• Deployment – Making results accessible and usable
Level: Designed for those wanting a deeper dive into real-world, data-driven workflows.