Modules

15 results

Elective Modules15

Approximate Dynamic Programming and Reinforcement LearningNo ratings for this module yet.Data AnalyticsYou will learn methods of Approximate Dynamic Programming (ADP) and Reinforcement Learning (RL) to solve sequential decision problems. In the end you will be able to describe fundamental models and algorithms, follow derivations, and implement simple ADP/RL methods and apply them to simple tasks (e.g., robotic).6 ECTSruns this semesterEI7649Business Analytics and Machine LearningNo ratings for this module yet.Data AnalyticsYou learn methods of statistical analysis and machine learning for classification, numerical prediction and clustering. After the module you can explain the assumptions and workings of common procedures and analyze datasets with R as well as interpret results.5 ECTSruns this semesterIN2028Data Mining und Knowledge DiscoveryNo ratings for this module yet.Data AnalyticsYou will learn methods of Data Mining and Knowledge Discovery: from data sources and quality through preprocessing, visualization and feature selection to correlation, regression, forecasting, classification and clustering. In the end you will be able to select appropriate methods, apply them and critically evaluate them, as well as deepen the foundations independently.3 ECTSruns this semesterIN2030Foundations and Application of Generative AINo ratings for this module yet.Data AnalyticsYou will learn the fundamentals and practical applications of generative AI, including modern models such as transformer architectures, Large Language Models, and Stable Diffusion. In the end you will be able to apply prompt engineering, load open-source models and fine-tune them, as well as assess opportunities, risks, and security aspects of generative AI.6 ECTSruns this semesterCITHN2014Fundamentals of Artificial IntelligenceNo ratings for this module yet.Data AnalyticsYou learn the foundations of artificial intelligence: from search procedures and constraint-satisfaction to logic and probabilistic models to decision making, learning and an introduction to robotics. In the end you will be able to design simple AI systems and apply basic methods from search, logic, probability and decision theory.runs this semesterIN2406
10 more in Elective ModulesMachine LearningNo ratings for this module yet.Data AnalyticsYou will learn the probabilistic foundations of machine learning and central learning algorithms — from simple neighborhood and clustering methods to linear models and support vector machines up to neural networks and the EM method. By the end you will be able to select, describe and derive suitable algorithms for given problems.8 ECTSruns this semesterIN2064Statistical LearningNo ratings for this module yet.Data AnalyticsYou learn the basics and advanced methods of supervised and unsupervised statistical learning. In the end you will be able to understand and apply models for regression and classification, use techniques for dimensionality reduction and cluster analysis, and follow probabilistic formulations of learning problems while designing new algorithms.6 ECTSruns this semesterMA4802Visual Data AnalyticsNo ratings for this module yet.Data AnalyticsYou will learn the entire visualization pipeline — from data acquisition and preprocessing over interpolation and filtering to presentation. You understand methods of information and scientific visualization for 2D/3D scalar and vector fields as well as terrain rendering and can evaluate and apply suitable techniques.5 ECTSruns this semesterIN2026Basic Mathematical Methods for Imaging and VisualizationNo ratings for this module yet.Data AnalyticsYou learn fundamental mathematical methods that are applied in imaging and visualization, and you can subsequently use them to formulate, analyze and solve concrete problems. Topics include, among others, linear algebra, analysis, optimization and probability theory and their applications in image processing and computer vision. In the end you will be able to select appropriate methods, optimize them and transfer them to related engineering disciplines.5 ECTSno date this semesterIN2124Computational StatisticsNo ratings for this module yet.Data AnalyticsYou will learn methods of computational statistics for high-dimensional, hierarchical, and latent data structures and how to apply them. The focus is on simulation (univariate and multivariate), Bayesian inference with MCMC (Gibbs, Metropolis-Hastings, Hamiltonian MC), bootstrap procedures and the EM algorithm for missing or latent data. In the end you can theoretically understand the algorithms, implement them in R, and interpret results statistically.5 ECTSno date this semesterMA4402Grundlagen von Computer VisionNo ratings for this module yet.Data AnalyticsYou will learn how images are formed and how to process image information for measurement and control tasks. The module covers surface properties, camera models and lenses as well as basic image processing and 3D reconstruction methods (stereo, shape from shading, structure-from-motion). In the end you will be able to calibrate camera systems and assess and apply methods for 3D reconstruction and image processing for robotic applications.4 ECTSno date this semesterIN2133Introduction to Mobile RoboticsNo ratings for this module yet.Data AnalyticsYou will learn how mobile, especially wheel-driven robots perceive their environment, map it, and move autonomously within it. In the end you can develop probabilistic sensor and motion models, apply filter methods for localization and SLAM, and implement fundamental methods for path planning and obstacle avoidance.6 ECTSno date this semesterCIT3330000Maschinelles Lernen für ComputersehenNo ratings for this module yet.Data AnalyticsYou will learn fundamental machine learning methods that are frequently used in computer vision (e.g., object classification, segmentation, denoising, camera calibration). In the end you will be able to explain the mathematical formulation of central procedures, create simple implementations, and apply them to concrete datasets from the field of computer vision.5 ECTSno date this semesterIN2357Modelling and SimulationNo ratings for this module yet.Data AnalyticsYou learn how to transfer real problems into formal models (mathematical or computational) and to process these models with suitable simulation strategies computationally. By the end of the module you will be able to distinguish model classes, develop simple solution procedures and select and apply simulation methods.8 ECTSno date this semesterIN2010Signal Processing and Machine LearningNo ratings for this module yet.Data AnalyticsYou will learn advanced mathematical methods, concepts and algorithms from signal processing and machine learning and apply them. The focus is on the integration of both paradigms with applications in communication and data processing. In the end, you can reformulate typical problem statements, apply suitable algorithms (e.g., for sparse signal processing or neural networks) and evaluate their results.5 ECTSno date this semesterEI70380
4 more modules match, but they are taught in German. Show themAnerkennung aus dem Ausland aus dem Bereich Data AnalyticsNo ratings for this module yet.Data Analyticsno date this semesterIN99645Anerkennung aus dem Ausland aus dem Bereich Data AnalyticsNo ratings for this module yet.Data Analyticsno date this semesterIN99646Bildverstehen I: Methoden der industriellen BildverarbeitungNo ratings for this module yet.Data AnalyticsDu lernst praxisrelevante Methoden und Algorithmen der industriellen Bildverarbeitung kennen. Im Modul werden Verfahren zur Lageerkennung, Form- und Maßprüfung sowie Objekterkennung behandelt. Am Ende kannst du Bildverarbeitungsaufgaben analysieren, bewerten und mit geeigneter Hardware und Algorithmen umsetzen.3 ECTSno date this semesterIN2023Industrielle BildverarbeitungNo ratings for this module yet.Data AnalyticsIn dem Modul lernst Du praxisrelevante Methoden und Algorithmen der industriellen Bildverarbeitung kennen. Du verstehst die typischen Einsatzgebiete (z. B. Lageerkennung, Form- und Maßprüfung, Beschriftungs- und Objekterkennung) und kannst Bildverarbeitungsaufgaben analysieren, bewerten und Lösungen entwickeln.6 ECTSruns this semesterIN2369