2025/2026
Neural Networks and Deep Learning
Type:
Mago-Lego
Delivered by:
Department of Business Informatics
When:
1, 2 module
Open to:
students of one campus
Instructors:
Seungmin Jin
Language:
English
ECTS credits:
6
Contact hours:
48
Course Syllabus
Abstract
This course introduces Master's students in Business Informatics—especially those with non-technical backgrounds—to neural networks and deep learning through an intuitive, low-code lens. Emphasizing practical training over coding expertise, it leverages ChatGPT for prompt engineering, code generation, and natural-language explanations to demystify algorithms like MLPs, CNNs, RNNs, and transformers. Students will explore forward/backpropagation, model architectures, and applications in business scenarios such as forecasting, image analysis, and anomaly detection.
Outcomes include: intuitive grasp of DL processes, low-code model training for business problems, ethical roadmaps, and a final prototype project. Ultimately, the course transforms deep learning from a technical hurdle into a strategic business tool, fostering analytics-driven innovation in resource-constrained environments.
cf. This course evaluates students using the normalized scores.