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Course title | City | Start date | Credits |
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Advanced Analysis Techniques | Kgs. Lyngby | - | 5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:The students will learn one or more advanced techniques for modeling and analysis of programs - thereby complementing their previous knowledge of modeling and analysis techniques, and giving them the background needed for judging |
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Advanced Topics in Machine Learning | Kgs. Lyngby | - | 2,5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:To introduce the student to new trends in statistical signal processing and machine learning.Learning objectives:A student who has met the objectives of the course will be able to:Comprehend and apply advanced methods within mach |
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Algebraic Graph Theory | Kgs. Lyngby | - | 5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:The course will provide students with the mathematical tools for applyingalgebraic techniques to graph theoretic questions. The main focus will be applying linearalgebraic tools to matrices associated to graphs in order to reveal |
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Applied computational data analysis | Kgs. Lyngby | - | 5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:To provide the student knowledge of advanced computer intensive data analysis methods with applications to e.g. life sciences. To apply the methods on a problem with own data.Learning objectives:A student who has met the objectiv |
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Convex optimization | Kgs. Lyngby | - | 5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:The aim of the course is to provide students with a general overview of convex optimization theory, its applications, and computational methods for large-scale optimization. The students will learn how to recognize convex optimiz |
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DTU Compute Academic Writing Bootcamp | Kgs. Lyngby | - | 2,5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:The course aims to improve participants’ writing processes by training meta-reflection on the participants own writing process. This is done both theoretically by the introduction of research based mental models and by practice o |
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DTU Compute PhD Seminar | Kgs. Lyngby | - | 2,5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:The aim of this course is to give a broad introduction to the life as a PhD student. The focus is on a number of topics and specific that are vital for the PhD student’s work and future career. Moreover, the coourse gives an intr |
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Generative Modeling Summer School (GeMMS) | Kgs. Lyngby | - | 5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:The summer school is targeted toward PhD students working with data science broadly and for whom generative modelling potentially plays a part in their projects. The objective of the course is to introduce the students to the bas |
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Introduction to applied statistics and R for PhD students | Kgs. Lyngby | - | 5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:Make the participants able to perform a standard statistical analysis of their own data and relate the results to the practical application. The participants will be able to carry out statistical analyses using the statistical pa |
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Introduction to Bayesian inverse problems | Kgs. Lyngby | - | 5 ECTS |
DTU Department of Informatics and Mathematical Modeling
General course objectives:Bayesian inversion is the technology of characterization and management of randomness in computational models of real-world applications. It blends theories and methods across stochastic analysis, statistical modeling and scienti |