Course: Mining Media Data II
This course, offered as part of the Master’s Program in Human Centered Intelligent Systems and Media Informatics at the Bonn-Aachen International Center for Information Technology (B-IT) as well as the Master’s Program in Computer Science at the University of Bonn, explores advanced techniques in data mining, emphasizing predictive and prescriptive methods applied to media data. Students will learn to analyze large and complex datasets using state-of-the-art machine learning methodologies, including behavioral prediction, knowledge distillation, and large language models (LLMs). The curriculum includes foundational concepts, text representation learning, transformer architectures, and practical applications in media analytics, such as recommendation systems and information extraction. The course combines theoretical instruction with hands-on exercises to develop both technical and analytical skills relevant to industry and research.
Course topics
- Understand and implement foundational models for a range of predictive and prescriptive data mining tasks.
- Study advanced methods for training and extending learning systems using intelligent optimization techniques.
- Analyze media data to derive actionable insights and support decision-making in real-world domains such as digital marketing, financial data analysis, and text/document analytics.
- Tackle key challenges in media analytics, including ethical issues, model interpretability, and efficient use of computational resources.
| Lecture | Date | Lecture Content |
|---|---|---|
| Lecture 1 | 30.4.2026 | Course Intro |
| Lecture 2 | 7.5.2026 | Data Mining Applications 1 |
| Lecture 3 | 21.5.2026 | Data Mining Applications 2 |
| Lecture 4 | 11.6.2026 | Representation Learning with Transformers 1: Intro and Training |
| Lecture 5 | 18.6.2026 | Representation Learning with Transformers 2: Textual Embeddings |
| Lecture 6 | 18.6.2026 | Representation Learning with Transformers 3: Text mining and NLP |
| Lecture 7 | 25.6.2026 | Representation Learning with Transformers 4: Multimodality |
| Lecture 8 | 25.6.2026 | Representation Learning with Transformers 5: Big Data Engineering in the age of LLMs |
| Lecture 9 | 9.7.2026 | RL and LLMs 1 |
| Lecture 10 | 16.7.2026 | RL and LLMs 2 |
| Lecture 11 | 23.7.2026 | Information Extraction and Practical Applications |
Lecure Notes
- Lecture 01: ZIP Download
- Lecture 02: ZIP Download