Directly to:
Semester (1 up to 4): |
1 |
2 |
3 |
4 |
|
Mandatory modules | Credit Points ECTS | ||||
---|---|---|---|---|---|
Advanced Mathematics (Module 1) | 6 | ||||
Geomatics Methodology (Module 2) | 15 | ||||
Signal Processing | (5) | ||||
Statistical Inference | (5) | ||||
Dynamic System Estimation | (5) | ||||
Engineering Geodesy (Module 3) | 9 | ||||
Monitoring | (3) | ||||
Kinematic Measurement Systems | (6) | ||||
Geodesy (Module 4) | 9 | ||||
Map Projections & Geodetic Coordinate Systems | (5) | ||||
Physical Geodesy | (4) | ||||
Remote Data Acquisition (Module 5) | 9 | ||||
Remote Sensing | (4.5) | ||||
Airborne Data Acquisition | (4.5) | ||||
Representation of Geodata (Module 6) | 9 | ||||
Geoinformatics | (6) | ||||
Thematic Cartography | (3) | ||||
Integrated Project (Module 7) | 6 | ||||
Information and Contract Law (Module 12) | 3 | ||||
German as a Foreign Language (Module 13) | 6 | ||||
Elective modules | |||||
Multisensor Integration in Geodesy and Transport (Module 8) | 9 | ||||
Terrestrial Multisensor Systems | (4.5) | ||||
Transport Telematics | (4.5) | ||||
Satellite Geodesy (Module 9) | 9 | ||||
Foundations of Satellite Geodesy | (4.5) | ||||
Satellite Geodesy Observation Techniques | (4.5) | ||||
Navigation (Module 10) | 9 | ||||
Satellite Navigation | (4.5) | ||||
Integrated Positioning and Navigation | (4.5) | ||||
Computer Vision and Pattern Recognition (Module 11) | 9 | ||||
Computer Vision | (4.5) | ||||
Pattern Recognition | (4.5) | ||||
M.Sc.-Thesis | Master thesis | 30 | |||
Credit Points ECTS/Sem | 30 | 30 | 30 | 30 |
Modules
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Advanced Mathematics | 1/WS | 3/2 | 6 | Lecture [412101] Lab [412102] |
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Module coordinator | Prof. Foster | ||||
Objectives | The module aims at establishing a common level of math skills for all students, smoothing out their individual entry levels. The module will provide secure skills in calculus, potential theory, theory of differential equations and Fourier analysis for later use in the other modules of the GEOENGINE curriculum. | ||||
Content | Ordinary and partial differential equations, Vector analysis, Integral theorems, Special functions, Potential theory | ||||
Assessment - type of examination - pre-qualifications |
- written examination, 120min, [41211], end of Semester 1/WS - term works |
Weights 1(1) |
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Statistical Inference | 1/WS | 2/1 | 5 | Lecture [412201] Lab [412202] |
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Dynamic System Estimation | 2/SS | 2/1 | 5 | Lecture [412203] Lab [412204] |
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Signal Processing | 1/WS | 2/1 | 5 | Lecture [412205] Lab [412206] |
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Module coordinator | Prof. Hobiger | ||||
Objectives | This module conveys advanced skills in statistical analysis and optimal processing of geodetic observations. From the different module sections the student will gain deeper knowledge and experience in the mathematical concepts of static and dynamic modeling approaches. This enables the student to solve for a wide range of problems in the field of network adjustments, Kalman filtering and digital image processing. | ||||
Content | Statistical Inference Basics on linear algebra, parameter adjustment, condition adjustment and mixed model adjustment, random varia-bles, probability density functions, error propagation, hypothesis testing, internal and external reliability Dynamic System Estimation Review of parameter estimation within the Gauß-Markov-Model, sequential parameter estimation, linear Ordinary Differential Equation Systems, linear/linearized dynamic models, Stochastic Processes, Power Spectral Density, filters, smoothing procedures, Kalman Filter Signal Processing Characterization of digital signals in space and frequency domain, sampling, interpolation of discrete signals, digital filters, recursive filters, signal smoothing, Kalman filtering, introduction to the MATLAB signal processing toolbox |
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Assessment - type of examination - pre-qualifications |
- written examination, Statistical Inference and Signal Processing, 120min [41221], end of Semester 1/WS - written examination, Dynamic System Estimation, 60min [41222], end of Semester 2/SS - term work Statistical Inference - term work Dynamic System Estimation - term work Signal Processing |
Weights 2(3) 1(3) |
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Monitoring | 1/WS | 1/1 | 3 | Lecture [484001] Lab [484002] |
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Kinematic Measurement Systems | 2/SS | 2/2 | 6 | Lecture [484003] Lab [484004] |
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Module coordinator | Prof. Schwieger | ||||
Objectives | The students are able to understand the principle of monitoring sensors, apply them for monitoring tasks and realize deformation analysis in the congruency model. Additionally they know all the details about positioning, filtering and controlling within kinematic measurement systems with a special focus on total stations. | ||||
Content | Monitoring Monitoring networks and point determination, Inclination measurements, Hydrostatical leveling, Alignment, plumbing methods, additional sensors, Monitoring analysis using the congruency model: two- and multi-epoch , comparison, global test, sensitivity test for localization of deformations, Graphical programming: introduction and data acquisition, Recapitulation of tachymeter techniques and measurements, Robot total stations, GNSS Kinematic Measurement Systems Kinematic measurement systems, Positioning for moving objCredit Points (ECTS) , Vehicle models, Prediction and filtering, e.g. Kalman filter, Basics of control theory, Integration of kinematic measurements into control circles, Construction machine guidance, Project at construction machine simulator of IIGS |
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Assessment - type of examination - pre-qualifications |
- written examination, Engineering Geodesy, 120min [48401], end of Semester 2/SS - term work Monitoring - term work Kinematic Measurement Systems |
Weights 1(1) |
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Map Projections & Geodetic Coordinate Systems | 1/WS | 2/1 | 5 | Lecture [412301] Lab [412302] |
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Physical Geodesy | 2/SS | 2/1 | 4 | Lecture [412303] Lab [412304] |
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Module coordinator | Prof. Sneeuw | ||||
Objectives | This module provides the student with profound knowledge of classical and modern geodetic concepts. Through the individual module sections the student will appreciate the fundamental role of coordinate systems and coordinate frames in geomatics engineering. | ||||
Content | Map Projections and Geodetic Coordinate Systems Basics on differential geometry of surfaces, geometry of sphere and ellipsoid-of-revolution, spherical map projections, optimal map projections, legal map projections (Gauß-Krüger/UTM), deformations and deformation measures, 2D and 3D coordinate systems and datum transformation models Physical Geodesy Elements of potential theory, gravitation and gravity, measurement principles of gravimetry, gravity networks, approaches to solving the Laplace equation, geoid determination, height systems |
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Assessment - type of examination - pre-qualifications |
- written examination, Geodesy, 120min [41231], end of Semester 2/SS - term work Map Projections & Geodetic Coordinate Systems - term work Physical Geodesy |
Weights 1(1) |
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Remote Sensing | 2/SS | 2/1 | 4.5 | Lecture [412401] Lab [412402] |
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Airborne Data Acquisition | 2/SS | 2/1 | 4.5 | Lecture [412403] Lab [412404] |
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Module coordinator | Prof. Sörgel | ||||
Objectives | The objective of this module is to provide the student with a thorough understanding of methods and modern instrumentation for the acquisition of spatial data using airborne and space-borne platforms. | ||||
Content | Airborne Data Acquisition Principles of airborne kinematic GNSS, PPP solutions, basics of IMU, GNSS/IMU integration, bundle block adjustment, camera calibration using additional parameters, Image matching: 2D correlation, least-squares and feature-based matching, semi-global matching. Automatic aerial triangulation and generation of dense surface models, orthophoto generation, airborne LiDAR, RADAR data collection, integration of RADAR and optical imagery. Remote Sensing history of RS and an overview of modern RS systems, orbits of RS satellites, sources of electromagnetic (EM) radiation, propagation of EM radiation, interaction of EM radiation with matter, detection and measurement of EM radiation, analog to digital conversion, data transmission and storage |
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Assessment - type of examination - pre-qualifications |
- written examination, Remote Data Acquisition, 120min [41241], end of Semester 2/SS - term work Airborne Data Acquisition - term work Remote Sensing |
Weights 1(1) |
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Geoinformatics | 3/WS | 2/2 | 6 | Lecture [412501] Lab [412502] |
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Thematic Cartography | 3/WS | 1/1 | 3 | Lecture [412503] Lab [412504] |
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Module coordinator | Dr. Walter | ||||
Objectives | Within this module the students will understand the methods and technologies of spatial data handling, analysis and presentation. The students will be enabled to acquire the relevant geodata for a complex application and to perform the appropriate geometric, topologic and thematic modeling, analysis and presentation. | ||||
Content | Geoinformatics Virtual Globes, Web 2.0 Technologies, Spatial Data Infrastructures, Web-APIs, Web-Services, Semantic Web, Database Management Systems, Database Design, Relational Model, SQL, Transaction Concept, GeoDBMS Thematic Cartography Analysis for information systems requirements (focus on thematic maps), Scientific cartography, cognitive maps, structure of the geo-data market, Techniques of homogenizing data sets (matching and merging), Map design, animated maps, thematic maps for individual and public transport |
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Assessment - type of examination - pre-qualifications |
- written examination, Representation of Geodata, 120min [41251], end of Semester 3/WS - term work Geoinformatics - term work Thematic Cartography |
Weights 1(1) |
Compulsory | |||||
---|---|---|---|---|---|
Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Integrated Project | 2/SS | Project, 10 days | 6 | Project [412801] | |
Module coordinator | Prof. Schwieger | ||||
Objectives | This module is the synthesis of all knowledge acquired in previous modules. It enables students to analyze real-life Geomantic Engineering tasks and to solve those tasks and problems with an engineering approaching an autonomous way. | ||||
Content | Variable topics are treated in projCredit Points (ECTS); e.g. "geoid determination" and "stake out of a tunnel". The student work for ten days on the project that is structured by several working packages. The planning, measurement, evaluation and analysis are realized in small teams. The students take care about the project management in different organisational levels. The academic staff member act as mentors and not as teachers. | ||||
Assessment - type of examination |
- integrated project [41281], non-graded course work |
Weights 1(1) |
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Remarks | The practical part of this module takes place at the end of the lecture period of second semester, i.e. in July each year (10 days field work). Final presentations / report will be delivered in October, typically. The project is classified as non-graded course work ("unbenotete Studienleistung USL"). |
Elective | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Terrestrial Multisensor Systems | 3/WS | 2/1 | 4.5 | Lecture [778001] Lab [778002] |
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Transport Telematics | 3/WS | 2/1 | 4.5 | Lecture [778003] Lab [778004] |
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Module coordinator | Dr. Zhang | ||||
Objectives | Terrestrial Multisensor Systems: MultiBased on the information provided in this module, the students are able to build up a terrestrial multi-sensor system. They understand the different sensors and their interaction as well as their handling within the system. Transport Telematics: The students are able to realize algorithms for positioning, navigation and routing. They know the structures of digital maps, which are necessary for Transport Telematics as well as some example sources. Besides they know about the interaction of different information sources as well as communication possibilities for transportation applications |
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Content | Terrestrial Multisensor Systems Definition of terrestrial multisensor systems, analogue and digital data registration, bus-based systems, analogue-digital conversion, special kinematic sensors, dead reckoning, coordinate systems, sensor corrections and reductions, synchronisation, real time data processing, evaluation using Kalman filter, project: development of a multisensor system Transport Telematics Digital road network, Communication technologies, Positioning and navigation systems, Traffic management systems, computer assisted operational control systems, Information services for traffic, driver assistance systems |
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Assessment - type of examination - pre-qualifications |
- written examination, Multisensor Integration in Geodesy and Transport, 120min [77801], end of Semester 3/WS - term work Terrestrial Multisensor Systems - term work Transport Telematics |
Weights 1(1) |
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Remarks | Only two out of the four offered elective modules (modules 8 - 11) have to be selected. |
Elective | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Foundations of Satellite Geodesy | 3/WS | 2/1 | 4.5 | Lecture [484201] Lab [484202] |
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Satellite Geodesy Observation Techniques | 3/WS | 2/1 | 4.5 | Lecture [484203] Lab [484204] |
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Module coordinator | Prof. Sneeuw | ||||
Objectives | The module aims at an understanding of the interplay between space-observation techniques, the related reference systems and the error sources degrading the observations. The students will learn to apply and assess space techniques for position acquisition with a sound knowledge of the available techniques of error mitigation. | ||||
Content | Foundations of Satellite Geodesy Time systems, Reference systems and reference frames, Signal propagation, Orbital motion Satellite Geodesy Observation Techniques Satellite Laser Ranging, normal points, satellite altimetry, sea surface topography, crossover analysis, very long baseline interferometry, correlation, Global Positioning System, ground segment, space segment, user segment, Pseudo Random Code, P-Code, C/A-Code, ephemeris data, Code Delay Loop, Costas Loop, pseudorange from code- and phase observations, linear combination, navigation solution, dilution of precision, single difference solution, double difference solution, cycle-slip detection ambiguities, error budget, ionospheric und tropospheric delays, multipath |
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Assessment - type of examination - pre-qualifications |
- written examination, Satellite Geodesy, 120min [48421], end of Semester 3/WS - term work Foundations of Satellite Geodesy - term work Satellite Geodesy Observation Techniques |
Weights 1(1) |
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Remarks | Only two out of the four offered elective modules (modules 8 - 11) have to be selected. |
Elective | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Satellite Navigation | 3/WS | 2/1 | 4.5 | Lecture [484301] Lab [484302] |
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Integrated Positioning and Navigation | 3/WS | 2/1 | 4.5 | Lecture [484303] Lab [484304] |
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Module coordinator | Prof. Hobiger | ||||
Objectives | Students have a complete understanding of all aspects of satellite navigation with modern Global Navigation Satellite Systems (GNSS) like GPS or Glonass and a basic understanding of the mathematical and physical background of Strap-Down Inertial Navigation Systems (INS). Based on this the students know the GNSS position accuracy limitations and the potential for error corrections by DGNSS. They understand the error behavior of INS with different types of inertial sensors, and the need to integrate such systems with external update measurements. | ||||
Content | Satellite Navigation Definition and realization of global coordinate systems for GNSS, satellite orbits and orbit parameters, GNSS signal generation and modulation, signal propagation, ionospheric and tropospheric refraction, signal reception and pseudorange measurements, modeling of pseudorange measurements, position determination, position error assessment, DGNSS Integrated Positioning and Navigation Coordinate systems (inertial, ECEF, local level, body, platform), parameterisation of transformations and rotations, rotational velocity, Strap-Down-Navigator differential equations, inertial sensors, integration of differential equations, error control, integration with externally provided positions. |
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Assessment - type of examination - pre-qualifications |
- written examination, Navigation, 120min [48431], end of Semester 3/WS - term work Satellite Navigation - term work Integrated Positioning and Navigation |
Weights 1(1) |
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Remarks | Only two out of the four offered elective modules (modules 8 - 11) have to be selected. |
Elective | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Computer Vision | 3/WS | 2/1 | 4.5 | Lecture [777901] Lab [777902] |
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Pattern Recognition | 3/WS | 2/1 | 4.5 | Lecture [777903] Lab [777904] |
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Module coordinator | Prof. Sörgel | ||||
Objectives | Within this module, the students will understand the automated methods and technologies of computer vision and pattern recognition. This comprises on the one hand image matching and orientation by means of approaches like structure from motion and 3D reconstruction by dense image matching. On the other hand, students will be able to scan large data amounts to identify certain classes of interest by means of feature selection and clustering. | ||||
Content | Computer Vision Automatic image matching by intensity and feature based methods, automatic image orientation by Structure-from-Motion, image based 3D surface reconstruction using dense multi-view stereo, image segmentation Pattern Recognition Feature space, different types of features, curse of dimensionality, Model based and statistical methods, supervised and unsupervised classification, Classification methods: Minimum distance, maximum likelihood, Bayes, decision tree, random forest, support vector machine, neural networks, and random fields, confusion matrix, overall accuracy, producer’s and user’s accuracy |
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Assessment - type of examination - pre-qualifications |
- oral examination, Computer Vision and Pattern Recognition, 40min [77791], end of Semester 3/WS - term work Computer Vision - term work Pattern Recognition |
Weights 1(1) |
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Remarks | Only two out of the four offered elective modules (modules 8 - 11) have to be selected. |
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Information and Contract Law | 3/WS | 2/0 | 3 | Lecture [484401] | |
Module coordinator | Horst Speichert | ||||
Objectives | The module imparts basic features of the contract, media and internet law. The student learns to recognize the separate functions and business processes, their main subjects and their duties and responsibilities. This results in a better understanding of the role and use of information technology in businesses across all functions. Students are made familiar with methods for lawful contracts and contracts checking, especially with regard to future management positions. | ||||
Content | Objectives and mechanism of law, the legal system (overview), the system of national law, the European system of law, international law. General remarks on contracts, requirements for a contract in general, terms of contract, irregularities in the perfor-mance of the contract, types of contract, disputes, arbitration, law-suits. General remarks tort liability based on fault, product liability. Selected fields of law (overview): Labour law, the law of business associations, competition law, copyright, patent, brands and related rights, data protection, other areas of interest (i.e. new European legislation on e-commerce). | ||||
Assessment - type of examination |
- written examination / graded course work, Information and Contract Law, 60min [48441], end of Semester 3/WS |
Weights 1(1) |
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Remarks | The course is offered as 1-week block course, right after the end of the lecture period in third semester (February each year). The written exam is classified as graded course work ("benotete Studienleistung BSL"). |
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
German language course | 1/WS | Intensive Course, 5 weeks | 6 | Intensive German Course [484501] | |
Module coordinator | Dr. Herrmann | ||||
Objectives | Students are able to converse about everyday situations in their studies and home, read and understand simple texts, have a command of basic grammar structures, and write about life and culture in the German speaking countries. | ||||
Content | The course aims to develop the four communication skills listening, speaking, reading, and writing, with an increased emphasis on conversational German. Students are exposed to everyday and professional situations. Students learn frequently used expressions related to areas of most immediate relevance. | ||||
Assessment - type of examination |
- written examination / non-graded course work, German as a Foreign Language, [48451], before start of lecture period of Semester 1/WS |
Weights 1(1) |
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Remarks | The course is offered as 5-week block course, right before start of the regular lectures in first semester (September/October each year). The written exam is classified as non-graded course work ("unbenotete Studienleistung USL"). |
Compulsory | |||||
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Module sections | Semester | SWS Lecture/Lab | Credit Points (ECTS) | Course Numbers | |
Master Thesis | 4/SS | 6 months | 30 | Thesis [80920] | |
Module coordinator | Prof. Haala, Prof. Hobiger, Prof. Schwieger, Prof. Sneeuw, Prof. Sörgel (according to thesis topic) | ||||
Objectives | The candidates are to demonstrate their ability to complete and document a well-defined research project within a given time frame. | ||||
Content | According to the thesis topic | ||||
Assessment - type of examination |
- Master Thesis, [3999], end of Semester 4/SS |
Weights 1(1) |
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Remarks | In order to start the Master Thesis project, the student has to have at least 60 credit points (ECTS). |
For details please access the course content information package (V9/2018)
or the most recent version of the full module handbook via C@MPUS directly