Our taught modules at the University of Bremen and through public channels teach the breath of lifelong machine learning, transport the necessary expertise in e.g. deep generative modeling, and are centered towards overall AI sustainability.
Below, we list the modules taught in each summer and winter semester cycle, followed by select formats available publicly. The respective course language is indicated in brackets.
Summer term
Vorlesung: Nachhaltigkeit und KI (De)
Wie interagieren KI und Nachhaltigkeit? Der Kurs spannt gleichermaßen, wie KI Nachhaltigkeitsziele fördern oder gefährden kann, und, wie Nachhaltigkeits-anforderungen die KI-Entwicklung beeinflussen. Hierfür werden sozio-technische Konzepte entlang der Gestaltung von KI-Systemen von Datenerhebung, zur Modelloptimierung, bis hin zur Evaluation eingeführt.
Lecture: Lifelong Machine Learning (En)
Whereas ML has traditionally concentrated on static pre-defined datasets and respective test scenarios, recent advances also take into account an evolving world. The course traverses the fundamentals of lifelong machine learning, spanning methodology of how to effectively learn in the present, remember past knowledge, and anticipate unknown future contexts and situations.
Seminar: Modern Perspectives on AI Sustainability (En)
The seminar covers different aspects of AI sustainability. Students will get to engage with a variety of modern perspectives. Throughout the seminar, they will learn to critically engage with current assessments on AI’s impact, analyze the validity of claims with respect to economical, environmental and social sustainability, and separate opportunities from unaddressed harms.
Project: MOCCA (En, spans the entire year)
In the Multi-Objective Continual Coffee Automation student project, we will make use of various machine learning tools to go from a package of coffee beans to drinks that are catered to individual preferences. This involves several crucial steps that will be pursued in the project, spanning data acquisition & dataset creation, continual machine learning, inclusion of preferences and natural language feedback.
Winter term
Vorlesung: KI: Transformer der Informatik (De)
Studierende werden einen grundlegenden Überblick darüber erhalten wie KI die Methodik der Informatik (und darüber hinaus) verändert und Anwendungen eröffnet: Bildgebende Verfahren, Sprache, Programmieren, Datenschutz, Ethik, Nachhaltigkeit, Hardware, KI + Wissenschaft, etc.
Lecture: Deep Generative Models (En)
The course will span materials on why generative models are critical, independently of whether the goal is to arrive at a decision or to generate data. We will cover the different ways to design generative models and respective mathematical tools necessary for understanding
Seminar: Advances in Lifelong Learning Machines (En)
Throughout the seminar, students will engage with modern literature that
advances the frontiers of lifelong learning machines. They will improve their presentation skills, navigating scientific works, inspect the newest
algorithms, and identify persisting limitations and open research questions.
Blockkurs: Propädeutikum Python (De)
Studierende lernen in Python geschriebene Programme zu lesen, zu verstehen und auszuführen. Sie lernen die Grundlagen von Datentypen, Funktionen, und Array Operationen, Umsetzung von mathematischen Beschreibungen, Visualisierung, und erste Schnittstellen kennen.
Publicly available courses
ESSAI 2023 Summer School: Machine Learning Beyond Static Datasets
A five day course offered at European Summer School on AI ESSAI 2023 from July 24th to July 28th in Ljubljana, Slovenia in a hybrid format. Lectures have been recorded as part of the summer school and are publicly available on their platform. All materials & links are provided on below course page.
Course: Continual Machine Learning – Summer 2022 at TU Darmstadt
The course 20-00-1135-vl was offered in person at TU Darmstadt in 2022 and simultaneously held as “Open World Lifelong Learning” live on YouTube. Lecture recordings and materials are available below. A playlist of all videos is also available through the ContinualAI Youtube channel.