Beginner or Advanced: Our machine learning training for your AI skills
Whether you're looking for a quick start or are looking for a first deep dive into machine learning: In machine learning training, we teach you everything you need to know about tried and tested machine learning workflows on Databricks at various depths. In this way, you start right where you are and get concrete results for your next steps. Both training variants are hands-on, adaptable to your setup (remote or on-site) and can be carried out with your data if you wish. In this way, we ensure that you can use the AI skills you have learned efficiently in everyday life.
Understanding machine learning
In this machine learning training for beginners, you will learn in practice how to successfully implement machine learning in Databricks: We will guide you through the entire development process — from preparing and analyzing the data to modeling and evaluation. We implement every step together directly in the notebook and record it reproducibly.
You will not only learn the most important concepts of machine learning, but also how to use them concretely and efficiently in Databricks. Previous knowledge of Python or SQL is helpful; we will explain everything else you need for the course in the context of the exercises.
You will not only learn the most important concepts of machine learning, but also how to use them concretely and efficiently in Databricks. Previous knowledge of Python or SQL is helpful; we will explain everything else you need for the course in the context of the exercises.
You will learn to clearly separate AI, classic ML and LLMs and to identify suitable use cases.
We'll introduce you to the key features of Databricks: from workspace and cluster setup to integrated AI/ML features.
You carry out exploratory analyses of a set of practice data: check distributions, make relationships visible and develop initial feature ideas.
We'll show you how to identify incorrect values, duplicate entries and outliers and correct them in a targeted manner using established transformation patterns and validation checks.
You train a machine-learning model and evaluate its performance using best practices such as train/test splits and cross-validation.
Perfecting machine learning
This training is aimed at teams with machine learning basics and Databricks experience and elevates your work to production levels. The focus is on better model performance (targeted model selection & tuning), clean experiment tracking with MLflow and stable operating routes (deployment & governance).
In this machine learning training, we combine theory with sophisticated hands-on exercises so that you end up with robust, versioned models and a clear operating and monitoring plan. Ideal if you prioritize performance, reproducibility, and operation.
In this machine learning training, we combine theory with sophisticated hands-on exercises so that you end up with robust, versioned models and a clear operating and monitoring plan. Ideal if you prioritize performance, reproducibility, and operation.
You choose the appropriate estimator and address under/overfitting in a targeted manner — e.g. with regularization and learning curves.
Systematic tuning with meaningful search spaces; the focus is on measurable gains compared to the baseline.
You version runs, parameters, metrics, and artifacts; experiments are transparently comparable and reproducible.
Batch or real-time? We use Unity Catalog for access, lineage, and compliance.
You transfer what you have learned to benchmark or your own data — the result is a clear implementation blueprint.
