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IRG - Information Retrieval GrundlagenB.Sc. (3rd year)Prof. Dr. Martin BraschlerZHAW School of EngineeringFoundations of Text Analysis and Retrieval: Analysing unstructured data.



DSSY - Decision Support SystemsB.Sc. (3rd year)Dr. Kurt Stockinger, Dr. Thilo StadelmannZHAW School of EngineeringData Warehousing & Big Data: Analyzing structured data.more
Grundlagen der künstlichen IntelligenzB.Sc. (3rd year)Prof. Dr. Malte Helmert

University of Basel

Die Vorlesung bietet eine Einführung in die grundlegenden Sichtweisen, Probleme, Methoden und Techniken der Künstlichen Intelligenz.

Thematische Schwerpunkte: Einführung und historische Entwicklung der KI, der Agentenbegriff in der KI, Problemlösen und Suche, Logik und Repräsentation, Handlungsplanung, Darstellung und Verarbeitung unsicheren Wissens.

Search and optimizationM.Sc.Prof. Dr. Malte HelmertUniversity of Basel

The seminar focuses on informed state-space search (search algorithms, heuristics).


Maschinelles Lernen in der Sprachverarbeitung


Dr. Simon Clematide

University of Zurich

An introduction to machine learning approaches including SVM, Logistic Regression, Graphical Models.


Quantitative Methoden in der Computerlinguistik


Dr. Manfred Klenner

University of Zurich

An introduction to statistics and machine learning (distributions, hypothesis testing; regression, maximum entropy).

Aktuelle Fragestellungen der statistikbasierten SemantikBachelorDr. Manfred KlennerUniversity of Zurich

Technics like Vector space and matrix factorization approaches (e.g. Latent Semantic Indexing) for the semantic modelling of natural languages.

XML Technologies and Semantic WebBachelor

Dr. Fabio Rinaldi

University of ZurichIntroduction to XML and the Semantic Web.more
Maschinelle Übersetzung und Parallele KorporaMaster

Prof. Dr. Martin Volk

University of Zurich

Overview on techniques in the field of statistical and hybrid machine translation and parallel corpora (e.g. parallel treebanks).

Human Language Technology: Applications to Information AccessDoctoral course (PhD)Dr. Andrei Popescu-BelisEPFL (EDEE and EDIC doctoral schools)This course introduces recent applications of human language technology, focusing on the problem of accessing text-based information across three main types of barriers: the quantity barrier, the crosslingual barrier, and the subjective barrier.more
Information RetrievalM.Sc.Prof. Dr. Stephane Marchand-Maillet

University of Geneva, Dept. of Computer Science

Fundemental aspects of Information Retrieval and associated Indexing.


Information Analysis and ProcessingM.Sc.Prof. Dr. Stephane Marchand-MailletUniversity of Geneva, Dept. of Computer ScienceFundemental aspects of Data Analysis and Information Theory.


Introduction to Artificial Intelligence

B.Sc. (3rd year)

Prof. Dr. Marc Pouly,

Prof. Dr. Jana Köhler

Lucerne University of Applied Sciences and Arts (HSLU)

Grundlegende Techniken zum Design und Implementation von intelligenten Agenten strukturiert nach Wissensrepräsentation, Problemlösung und Maschinelles Lernen. 

Themen sind u.a. Constraint Programmierung, Probabilistisches Schliessen, Planung und Scheduling, Regressionsanalyse, Neuronale Netze und Entscheidungsbäume. 

DAS in Data ScienceProf. educationDr. Kurt StockingerZHAW School of EngineeringDas Diploma of Advanced Studies (DAS) ist interdisziplinär aufgebaut und vermittelt Fähigkeiten etwa aus den Bereichen Data Warehousing & Big Data, Information Retrieval & Text Analytics sowie Statistics & Machine Learning. IT-Grundlagen, explorative Datenanalyse, Datenvisualisierung, Data Product Design und rechtlich-ethische Aspekte runden die Fähigkeiten als Daten-Allrounder ab.


Einführung in die Multilinguale TextanalyseMasterProf. Dr. Martin Volk University of ZurichThis course introduces the methods of automatic corpus annotation for both monolingual and multilingual corpora.


Techniken der Semantikanalyse MasterProf. Dr. Martin Volk University of Zurich This course introduces topics in the automatic semantic analysis of parallel corpora.


Master in Informatics / Intelligent SystemsMasterProf. Dr. Jürgen SchmidhuberUniversity of Lugano USI & Swiss AI Lab IDSIAA Master's in Computer Science, with a Focus on Artificial Intelligence. Taught by award-winning experts of the Swiss AI Lab, IDSIA, and the Faculty of Informatics at the University of Lugano (USI). In the scenic southern part of Switzerland, the world's leading science nation!


AIC - Automatisation avancée, intelligence artificielle et cognitiqueB.Sc. (3rd year) and C.E.Prof. Dr. Jean-Daniel DessimozHESSO HEIG-VDDéfinitions, et nombreux exemples; manipulations de laboratoires et relatives. Exemple clip vidéo: more
Intelligence ArtificielleB.Sc. (3rd year)Prof. Dr. Boi FaltingsEPFLIntroduction to AI (in French) using the book at
Intelligent AgentsMasterProf. Dr. Boi FaltingsEPFLTheory and practice of agent and multi-agent systems: reactive and deliberative agents, multi-agent systems, computational game theory. Includes a mini-project programmed in Java.more
Learning and Intelligent SystemsBachelorProf. Dr. Andreas KrauseETHZThe course introduces the foudations of learning and making predictions based on data.more
Data Mining: Learning from Large Data SetsMasterProf. Dr. Andreas KrauseETHZMany scientific and commercial applications require insights from massive, high-dimensional data sets. This courses introduces principled, state-of-the-art techniques from statistics, algorithms and discrete and convex optimization for learning from such large data sets. The course both covers theoretical foundations and practical applications.more
Probabilistic Artificial IntelligenceMasterProf. Dr. Andreas KrauseETHZThis course introduces core modeling techniques and algorithms from statistics, optimization, planning, and control and study applications in areas such as sensor networks, robotics, and the Internet.more
Computational StatisticsMaster Dr. Martin Mächler,
Prof. Dr. Peter L. Bühlmann 
ETHZ"Computational Statistics" deals with modern methods of data analysis (aka "data science") for prediction and inference. An overview of existing methodology is provided and also by the exercises, the student is taught to choose among possible models and about their algorithms and to validate them using graphical methods and simulation based approaches.more
Information RetrievalMasterProf. Dr. Thomas HofmannETHZIntroduction to information retrieval with a focus on text documents and images. Main topics comprise extraction of characteristic features from documents, index structures, retrieval models, search algorithms, benchmarking, and feedback mechanisms. Searching the web, images and XML collections demonstrate recent applications of information retrieval and their implementation.more
Big DataMasterProf. Dr. Thomas HofmannETHZOne of the key challenges of the information society is to turn data into information, information into knowledge, and knowledge into value. To turn data into value in this way involves collecting large volumes of data, possibly from many and diverse data sources, processing the data fast, and applying complex operations to the data.more
Probabilistic Graphical Models for Image AnalysisMasterDr. Brian Victor McWilliams ETHZThis course will focus on the algorithms for inference and learning with statistical models. We use a framework called probabilistic graphical models which include Bayesian Networks and Markov Random Fields. We will use examples from traditional vision problems such as image registration and image segmentation, as well as recent problems such as object recognition.more
Imaging and Computer VisionMasterProf. Dr. Gábor Székely
et al.
ETHZLight and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation and deformable shape matching. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition.more
Computer VisionMasterProf. Dr. Marc Pollefey,
Prof. Dr. Luc Van Gool
ETHZThe goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises.more
Statistical Learning TheoryMasterProf. Dr. Joachim M. Buhmann ETHZThe course covers advanced methods of statistical learning : PAC learning and statistical learning theory;variational methods and optimization, e.g., maximum entropy techniques, information bottleneck, deterministic and simulated annealing; clustering for vectorial, histogram and relational data; model selection; graphical models.more
Computational Intelligence LabMasterProf. Dr. Thomas HofmannETHZThis laboratory course teaches fundamental concepts in computational science and machine learning based on matrix factorization. This method provides a powerful framework of numerical linear algebra that encompasses many important techniques, such as dimension reduction, clustering, combinatorial optimization and sparse coding.more
Introduction to Natural Language ProcessingMasterDr. Enrique Alfonseca Cubero,
Dr. Massimiliano Ciaramita
ETHZThis course presents an introduction to general topics and techniques used in natural language processing today, primarily focusing on statistical approaches. The course provides an overview of the primary areas of research in language processing as well as a detailed exploration of the models and techniques used both in research and in commercial natural language systems.more
Pattern classification and machine learningDr. Mohammad Emtiyaz KhanEPFLPattern classification occupies a central role in machine learning from data. In this course, basic principles and methods underlying machine learning will be introduced. The student will learn few basic methods, how they relate to each other, and why they work. more
Information Engineering 1 & 2Bachelor 3rd yearProf. Dr. martin Braschler
et al.
ZHAW School of EngineeringInformation Engineering teaches foundational methods and processes to design and develop information systems. This includes creating, distributing and unlocking the information contained in structured and unstructured data.more
Economics and ComputationBSc + MScProf. Dr. Sven SeukenUniversity of ZurichIn this course, we cover the interplay between economic thinking and computational thinking. Topics covered include: game theory, mechanism design, p2p file-sharing, eBay auctions, advertising auctions, combinatorial auctions, matching markets, and computational social choice.more