Fortgeschrittene KI-basierte Anwendungssysteme - Data Science und Business Analytics - Einzelansicht

Vorlesungstermin: Donnerstag, 12-14Uhr im 3.06.H01.

Übungstermin: Donnerstag, 14-16Uhr im 3.06.S19.

Der Vorlesungs- und Übungsstart erfolgt am 17.10.2024.

Grum, M. (2022). Construction of a concept of neuronal modeling. Springer Nature.
https://doi.org/10.1007/978-3-658-35999-7

Weitere Literaturempfehlungen erfolgen themenspezifisch.

Basic knowledge of artificial intelligence and modeling of AI-based application systems is recommended - as it is provided by KIBAS course.

Written exam
Passing the exercise as a prerequisite for participation in the written exam according to the respective module regulations.

This advanced course deepens the understanding of the impact of Artificial Intelligence (AI) and other intelligent devices on the collection, analysis, processing and use of data in novel application systems. These changes are shaping the relationship between organizations and end users at strategic, tactical and operational levels, especially in the context of commercial activities.

The main objective of this course is to provide students with a comprehensive understanding of the technologies, concepts, methods, approaches and tools that lie within the data science, business analytics and AI context. Areas of focus include the following. First, an in-depth statistical study of the impact of AI at different levels, including individual users, companies, industries and economies in data-driven contexts. Second, the analysis of data science and machine learning techniques, especially neural networks, as well as big data techniques and the infrastructure of AI-enabled operating systems, system networks and organizations. Third, use and discussion of analytics frameworks (e.g. Python-based) and parallelization frameworks (e.g. TensorFlow, PyBrain, Spark) as well as expected strategies of leading companies in the virtual world such as Apple, Google, Facebook and Amazon as well as start-ups related to AI. Fourth, ethical issues will be addressed and emerging business models and their impact on the physical world will be examined. The course aims not only to impart knowledge and analytical skills, but also to develop judgment and design skills at all levels of sustainable management as well as software implementation. Students should be enabled to realize and design AI-based application systems in the field of business informatics as well as their exploration in a statistical experiment setting.

Hauptzielgruppen M.Sc. WIDT, M.Sc. Data Science