Christoph M. Flath

Interactive Teaching Materials

These interactive notebooks are built with marimo, a reactive Python notebook environment. They run entirely in your browser using WebAssembly - no installation required. Feel free to explore, modify, and experiment with the code.

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Datenmanagement & -analyse (DMA)

Session 1: SQL-Grundlagen → Session 1: SQL-Grundlagen — Lösungen → Session 2: SQL für Datenexploration → Session 2: SQL für Datenexploration — Lösungen → Session 3: Aggregation & Gruppierung → Session 5: Datenmodellierung → Session 6: Relationales Modell & Transformation → Session 7: Normalisierung → Session 8: JOINs → Session 8: JOINs — Lösungen → Session 9: Subqueries, Views & Transaktionen → Session 10: Strukturierte Datenanalyse → Session 11: Statistische Inferenz & A/B-Tests → Session 12: Zeitreihenanalyse → Session 13: Textanalyse →
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D3 in Practice (D3)

Rmexploration → Demand Management → Bookinglimits → Demand Management → D3Ip Case2 Rm 1 Data → D3Ip Case2 Rm 2 Dynamic → D3Ip Case2 Rm 3 Prediction → D3Ip Case2 Template →
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Planen und Entscheiden (PuE)

Übung 1: Grundlagen der Entscheidungstheorie → Übung 2: Deskriptive Entscheidungstheorie → Übung 3: Lineare Programmierung — Grafische Lösung → Übung 4: Simplex-Verfahren → Übung 5: LP mit PuLP → Übung 6: Sensitivitätsanalyse →
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Analytical Information Systems (AIS)

T01: SQL Exercises → T02: Data Integration & Quality → T03: Visualization & BI → T04: Capstone — Data to Dashboard → T05: Supervised Learning →
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Information Systems (IS)

Sna → SNA New ↗
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Optimization in Practice (OIP)

Sensitivity Analysis ↗ NW Petroleum ↗ FCC Supply Chain ↗ Bavarian Motor Company ↗ The Perfect Blend ↗ Cafe Emergency Exit ↗ Coffee Demand Regression ↗ Cafe 2.0 ↗ Cafe Rostering Basic ↗ OIP WLP Base ↗ Santa TSP MTZ ↗ Integer Programming ↗ Media Planning Optimization ↗
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Decision Support Systems (DSS)

DSS Kickoff Live ↗ Toy Factory PuLP ↗ Santa TSP Marimo ↗
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