Modules

41 results

A1.5 Minor41

Advanced Modeling, Optimization, and Simulation in Operations ManagementNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceIn this module you will learn quantitative methods for the analysis, control and optimization of production and service processes in the field of Operations Management. You will practice mixed-integer linear optimization with OPL/IBM ILOG CPLEX as well as discrete, event-driven simulations in AnyLogic, and you will be able to formulate, implement and evaluate results of models.6 ECTSruns this semesterWI001088Approximate Dynamic Programming and Reinforcement LearningNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou 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.A1.5.1 Modules in Economy, Computer ScienceYou 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.A1.5.1 Modules in Economy, Computer ScienceYou 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 semesterIN2030Efficient Algorithms and Data StructuresNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn the fundamentals of analyzing algorithms as well as central data structures and fundamental algorithmic problems. The focus is on runtime and space analysis, various search trees, hashing methods, priority queues, union-find structures, as well as maxflow/mincut and matching algorithms. In the end you will be able to analyze algorithms, assess the efficiency of data structures, and design new solutions for problems.8 ECTSruns this semesterIN2003
36 more in A1.5 MinorEnergy Markets INo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will gain a comprehensive overview of energy markets and industries across all commodities. You will learn value chains from primary energy supply to energy demand, central economic concepts, price formation, merit orders and organized energy trading. In the end you will be able to economically analyze energy-related problems and develop solution approaches using learned mathematical techniques.6 ECTSruns this semesterWI000946Games on GraphsNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn the theory of games on finite graphs. Building on reachability games, both qualitative and quantitative variants are treated, and in the end you will be able to apply the fundamental solution methods and solve smaller game instances on your own.5 ECTSruns this semesterIN2296Introduction to Deep LearningNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceIn this module you will learn the fundamentals and current methods of Deep Learning, with a special focus on neural networks and Convolutional Neural Networks. You understand theory (e.g. backpropagation, SGD, regularization) and acquire practical experience in training and optimizing network architectures, so you can solve simple applications such as digit recognition or image classification.6 ECTSruns this semesterIN2346Introduction to Deep Reinforcement LearningNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn the theory and fundamentals of Deep Reinforcement Learning (DRL) as well as relevant deep-learning and reinforcement-learning concepts. By the end you will be able to model problems as Markov Decision Processes, understand and apply DRL algorithms, and assess their advantages and disadvantages.6 ECTSruns this semesterMGT001299Logistics and Operations StrategyNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn how logistics and operational decisions are strategically anchored in the corporate and competitive environment. You will use models and optimization methods to analyze procurement, location, capacity, and network decisions, and you will derive robust strategies for different industries.6 ECTSruns this semesterWI000976Machine LearningNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou 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 semesterIN2064Stochastic Modeling and OptimizationNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn methods for decision support in stochastic multi-period environments. The module covers both the mathematical theory (e.g. stochastic processes, Markov decision processes, stochastic programming) and their application to practical problems such as inventory management or personnel planning. In the end, you can select suitable procedures, apply them, and assess their advantages and disadvantages.6 ECTSruns this semesterWI000977Strategies in MNEsNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will gain in-depth knowledge of central elements of corporate strategy and concepts and instruments for the management of multinational enterprises (MNEs). By the end of the module you will be able to analyse strategic questions of MNEs and develop well-founded strategy proposals, for example regarding portfolios, growth programs, and internationalisation.6 ECTSruns this semesterWI001128Transportation AnalyticsNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn how to formulate transport, routing and network planning problems as mixed-integer linear programs and solve them practically with algorithms. The module combines theory of problems (e.g., TSP, VRP, Network Design, Maritime Logistics) with implementation and numerical solution in a programming language.6 ECTSruns this semesterWI001193VerkehrsmanagementNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceIn the module you will learn to model traffic flows on highways and in cities and to plan and evaluate traffic control and management measures based on these models. In the end you will be able to apply traffic flow models and control procedures as well as assess the quality and effects of dynamic traffic information.6 ECTSruns this semesterBV560024Algorithmen für Uncertainty QuantificationNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn methods for quantifying uncertainties in computer-based simulations. In the end you will be able to place central algorithms for Forward Uncertainty Quantification, assess their complexity, and evaluate when which procedures (e.g., Monte Carlo, Quasi-Monte Carlo, stochastic collocation, stochastic Galerkin) are suitable.5 ECTSno date this semesterIN2345Auction Theory and Market DesignNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn game-theoretic fundamentals and mechanism design as well as the theory and practical realization of various auction and matching formats. In the end you will be able to explain properties and payment rules of open and closed auctions, model strategic interactions, and justify the selection of auction formats with regard to efficiency or revenue goals.5 ECTSno date this semesterIN2211Automaten und formale Sprachen IINo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou study advanced topics of automata theory, e.g. tree automata, weighted automata and automata for the verification of infinite state spaces. In the end you will be able to choose appropriate automata models, construct automata and apply automata-theoretic techniques to problems such as text analysis or program verification.5 ECTSno date this semesterIN2042Complexity TheoryNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn formal computational models (in particular Turing machines and circuits) as well as the most important complexity classes (e.g. L, NL, P, NP, PSPACE, EXP, NEXP, PH). By the end you will be able to analyze problems with respect to time and space complexity, apply reductions and completeness proofs, and classify advanced concepts such as alternation, randomized methods, and interactive proof systems.8 ECTSno date this semesterIN2007Computational Social ChoiceNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will become familiar with methods of collective decision making (Social Choice), with a focus on procedures that use majority relations and their algorithmic properties. In the end you will be able to analyze, compare, and assess the computational complexity of various election procedures.6 ECTSno date this semesterIN2229Computer Vision I: Variational MethodsNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn how many tasks of image processing (e.g. denoising, desmearing, segmentation, optical flow, stereo depth estimation, 3D reconstruction) are formulated and solved as variational problems. In the end you know the Euler–Lagrange approach and PDEs, efficient solution methods as well as convex formulations and relaxations and you can implement central concepts in Matlab.8 ECTSno date this semesterIN2246Computer Vision II: Multiple View Geometry (3D Computer Vision)No ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn the mathematical foundations of multiple-view geometry in order to reconstruct camera motion and 3D geometry from several images. In the end you will understand image formation, epipolar geometry, camera calibration, rank conditions and bundle adjustment and you will be able to implement central algorithms in Matlab.8 ECTSno date this semesterIN2228Convex Optimization LaboratoryNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will receive practical guidance on the design and implementation of algorithms for convex optimization with applications particularly from information and communication technology. In the end you will be able to mathematically model optimization problems, develop suitable solution methods and numerically implement them (including standard methods such as simplex, gradient descents, Newton methods and basic interior-point methods).6 ECTSno date this semesterEI72561Effiziente Algorithmen und Datenstrukturen IINo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn advanced algorithmic methods focusing on linear optimization and techniques for solving combinatorial problems. In the end you will be able to formulate linear models, apply classical solution methods such as the Simplex method and advanced methods like Ellipsoid and Karmarkar methods, and use approximation and rounding approaches for NP-complete problems.8 ECTSno date this semesterIN2004Energy EconomicsNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn economic fundamentals and methods for analyzing energy markets (e.g., gas, oil, coal, electricity). In the end you will be able to distinguish market structures and behaviors of producers and consumers, assess network regulation, and apply theoretical as well as empirical methods to current developments such as the energy transition.6 ECTSno date this semesterWI001145Energy Markets IINo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou deepen your understanding of energy and electricity markets with a focus on fundamental concepts such as promoting renewable energy, trading on wholesale markets, generation and grids. In the end you will be able to explain market mechanisms, trade energy commodities, classify the role of transmission networks and their regulation, and make decisions for energy suppliers.6 ECTSno date this semesterWI001125Fortgeschrittene Netzwerk- und Graph-AlgorithmenNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou deepen knowledge of graph and network algorithms: the focus is on centrality measures, density measurement algorithms in (sub)graphs, connectivity problems, and the assignment problem (Hungarian method). At the end you can analyze complex network problems, assess their complexity, and develop or apply suitable efficient algorithms.8 ECTSno date this semesterIN2158Grundlagen von Computer VisionNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou 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 semesterIN2133Konvexe Optimierung für Computer VisionNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn the fundamentals of convex analysis and their application to optimization problems in image processing and computer vision. After the module you will be able to understand, apply and implement common first-order and proximal methods for typical CV tasks (e.g., image reconstruction, segmentation, matrix factorization).6 ECTSno date this semesterIN2330Machine Learning for Graphs and Sequential DataNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn methods of machine learning for graph data and sequential data. You understand models for texts and temporal sequences as well as techniques for networks and graphs and can apply and evaluate them to real tasks. In the end you can select suitable procedures and assess their strengths/weaknesses for non-independent data.5 ECTSno date this semesterIN2323Maschinelles Lernen für ComputersehenNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou 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.A1.5.1 Modules in Economy, Computer ScienceYou 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 semesterIN2010Numerische Algorithmen für Computer Vision und Maschinelles LernenNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn numerical methods that are frequently used in computer vision and machine learning, including modeling of practical problems. In the end you will be able to implement basic algorithms, assess their strengths and weaknesses, and choose appropriate methods for solving concrete CV-/ML tasks.5 ECTSno date this semesterIN2384Online- und ApproximationsalgorithmenNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn fundamentals and advanced techniques of online and approximation algorithms. In the end you will know classical online problems (e.g., scheduling, paging, k-server), analysis tools such as amortized analysis and randomized algorithms, as well as design techniques for approximation algorithms including LP-relaxation and randomized rounding.8 ECTSno date this semesterIN2304Optimierungsverfahren - Simulation und Operations ResearchNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceIn this module you will learn methods of optimization and simulation: from analytical extremum problems through numerical optimization procedures to linear and nonlinear methods, search algorithms as well as fundamentals of simulation (deterministic, stochastic, event-directed). In the end you will be able to apply, analyze and further develop these methods to solve relevant tasks.3 ECTSno date this semesterBV130002Planning and Scheduling of Complex Operations: Models, Methods and ApplicationsNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn to model and solve complex planning and scheduling problems with limited resources. In the end you will be able to formulate common scheduling models, apply suitable solution methods (exact, heuristic, metaheuristic) and implement simple implementations as well as linear programs to solve real problems.6 ECTSno date this semesterWI200541Randomisierte AlgorithmenNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn fundamentals and techniques of randomized algorithms and how to estimate their running time and correctness with probabilistic methods. In the end you will be able to understand and analyze classical randomized algorithms (e.g., randomized Quicksort, Min-Cut, Treaps) and apply tools such as Markov, Chebyshev and Chernoff inequalities.8 ECTSno date this semesterIN2160Scheduling Manufacturing SystemsNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn how decisions on timing and deployment planning in production systems are systematically made using quantitative methods. In the end you can select and apply scheduling procedures to create and evaluate schedules for different layout types (e.g., assembly systems, process industry, AGV centers).6 ECTSno date this semesterMGT001371Social ComputingNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou learn the basics and methods of Social Computing: concepts of social media, social networking and social contexts as well as sociometric methods (centrality, density, clustering), metrics of real networks, models of social relationships in space and time, Social Signal Processing and fundamentals of game theory. In the end you will be able to apply these concepts to the conception, implementation and research of Social Computing applications.5 ECTSno date this semesterIN2241Stochastische OptimierungNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou will learn the basics and methods of stochastic optimization and practice formulating and numerically solving real decision problems under uncertainty as stochastic optimization problems. In the end you can understand two- and multi-stage models, incorporate risk measures, and apply solution approaches with software (MATLAB + numerical solvers).6 ECTSno date this semesterWI001135Transportation LogisticsNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceYou get an overview of central problems of goods and passenger transport logistics and learn basic modeling and solution approaches. In the end you will be able to formulate traffic, routing and network planning problems as mixed-integer linear programs and solve them practically with heuristics while interpreting the results.6 ECTSno date this semesterWI000978
1 more module matches, but it is taught in German. Show itEinsatz und Realisierung von DatenbanksystemenNo ratings for this module yet.A1.5.1 Modules in Economy, Computer ScienceDu lernst, wie moderne Datenbanksysteme aufgebaut und eingesetzt werden. Am Ende kannst Du wesentliche Komponenten (Transaktionsverwaltung, Recovery, Mehrbenutzersynchronisation, physische Organisation, Anfragebearbeitung) erklären, Algorithmen und Datenstrukturen implementieren sowie Einsatzszenarien kritisch bewerten und skizzieren.6 ECTSno date this semesterIN2031