What it is about
You will learn the entire lifecycle of an AI project for supervised machine learning — from problem formulation to productive, scalable deployment. Technical implementation in Python, collaboration between humans and AI, ethical considerations, as well as aspects of Generative AI and Large Language Models are addressed.
What you will be able to do
- Implement the complete lifecycle of a typical AI use case with supervised ML
- Understand productive and scalable deployment of ML solutions
- Classify Generative AI and Large Language Models in context
- Integrate Machine Learning into complex systems and collaboration of multiple entities
- Knowledge of ethics, bias and explainability in AI systems
- Apply typical Python programming safely for AI tasks
What the module consists of
- VorlesungConveying concepts, methods and overarching topics
- DiskussionenExchange on content, ethical aspects and practical questions
- gemeinsame ProgrammierübungenPractical application and deepening of the methods
- Hausaufgaben/ProgrammieraufgabenEnsuring implementation capabilities
Teaching method
- LecturesConveying the theoretical foundations
- Discussion roundsDeepening, reflection and critical engagement
- Shared programming exercisesJoint practical practice of the implementation
- Homework submissionsIndependent application and demonstration of practical skills