Big Data Algorithms and Systems
Lecturer | Prof. Dr. Andreas Siebert |
Type of course | Lecture / Tutorials |
ECTS credits | 5 |
Semester | Summer Semester |
Module Number | IB760 |
Admission Requirements | Algorithms and data structures Programming knowledge B2 Level in English |
Format | On Campus |
Objectives | The students will be able to understand, to analyze, and to apply algorithms that are taylored to large data sets. In particular, online algorithms, novel hashing algorithms, point algorithms, and string algorithms are covered. |
Bachelor Thesis
Lecturer |
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Type of course | Bachelor Thesis |
ECTS credits | 12 |
Semester | Winter Semester |
Module Number | IB720/ KI710 |
Admission Requirements | B2 Level in English |
Format | On Campus |
Objectives |
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Internet of Things
Lecturer | Prof. Dr. Abdelmajid Khelil |
Type of course | Lecture / Tutorials |
ECTS credits | 5 |
Semester | Summer Semester |
Module Number | IB674 |
Admission Requirements | B2 Level in English |
Format | On Campus |
Objectives | After successful completion of this course, students are able to:
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Innovation Lab (IoT-Project)
Lecturer | Prof. Dr. Abdelmajid Khelil |
ECTS | 5 |
Semester | Winter and Summer Semester |
Module Number | IB765 |
Admission Requirements | Experience in Software Enigneering and Programming B2 Level in English |
Format | On Campus |
Objectives | Throughout the course, students:
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Teaching Content | The cooperating companies offer the students real problems from the most important IoT domains, such as Smart Agriculture, Smart Building, Smart Energy, Smart Production, eHealth, etc. The problem is described in detail using defined application cases. In addition, the aspects of IoT Cloud and IoT Security are also examined. |
Study Project
Lecturer | Lecturers of CS |
ECTS | 5 |
Semester | Winter Semester, Summer Semester |
Module Number | IB351 |
Admission Requirements | Experience in Programming and Software Engineeering B2 Level in English |
Format | On Campus |
Objectives | After successful completion of this course, students:
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Content | The teachers of the Faculty of Computer Science offer the students a choice of project topics with a short description. Teams of students can propose a project themselves, for this you must find a supervising lecturer. The students are regularly supervised professionally by the issuing lecturer. |
Foundations of Scientific Work
Lecturer | Prof. Dr. Markus Böhm |
ECTS | 2 (Per Semester) |
Semester | Winter and Summer Semester |
Module Number | WIF290 |
Admission Requirements | -- |
Format | On Campus |
Objectives | Students are motivated to work scientifically and will be able to acquire subject-specific knowledge from the scientific literature and to prepare this knowledge for specific target groups.
1. Basics of scientific work Students understand the necessity of a scientific approach to problems and are able to understand the basic concepts of scientific work. (e.g. research questions, argumentation logic, writing style, citation) 2. Research methods Students are able to apply essential research methods commonly used in business informatics and to assess the basic applicability of these methods for a given problem. In addition, they understand the basics of design-oriented research (Design Science). Furthermore, they are able to conduct a systematic literature study on their own. 3. Handling of scientific texts Students can describe the structure of scientific texts, apply reading strategies and assess their basic scientific quality. Furthermore, they can compile, evaluate and compare the core statements of different scientific texts. 4. Presentation and discussion In the area of presentation and discussion, students understand the essential elements of effective presentations and are able to apply them to a lecture. In addition, they are able to apply argumentation strategies for professional discussions and methods for effective discussion moderation.
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Cloud Computing
Lecturer | Prof. Dr. Markus Mock |
Type of course | Lecture |
ECTS credits | 5 |
Semester | Summer Semester (2025) |
Module Number | IB768/KI620 |
Admission Requirements | B2 Level in English |
Format | On Campus |
Objectives |
Machine Learning in the Cloud
Lecturer | Prof. Dr. Markus Mock |
Type of course | Lecture |
ECTS credits | 5 |
Semester | Winter Semester (2024/2025) |
Module Number | KI720 |
Admission Requirements | B2 Level in English |
Format | On Campus |
Objectives |
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Machine Learning II
Lecturer | Prof. Dr. Sandra Eisenreich |
Type of course | Lecture |
ECTS credits | 8 |
Semester | Summer Semester (2025) |
Module Number | KI440 |
Admission Requirements | B2 Level in English |
Format | On Campus |
Objectives |
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Reinforcement Learning
Lecturer | Prof. Dr. Eduard Kromer |
Type of course | Lecture |
ECTS credits | 5 |
Semester | Winter Semester (2024/2025) |
Module Number | KI740 |
Admission Requirements | B2 Level in English |
Format | On Campus |
Objectives |
3D Game Engines
Lecturer | Prof. Dr. Christopher Auer |
Type of course | Lecture |
ECTS credits | 5 |
Semester | Summer Semester (2025) |
Module Number | KI630 |
Admission Requirements | B2 Level in English |
Format | On Campus |
Objectives |
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