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79692-01 - Kolloquium: Advanced Marketing Analytics (3 KP)
| Semester | Herbstsemester 2026 |
| Angebotsmuster | Jedes Herbstsemester |
| Dozierende | Andreas Lanz (andreas.lanz@unibas.ch, BeurteilerIn) |
| Inhalt | Building on the Marketing Analytics colloquium, the goal of this course is to transform you into a marketing professional that can engage in data-driven decision-making by means of advanced modeling. Using the statistical computing software R, one of the standard tools among data scientists, you will mine data––by means of advanced modeling––from a racing simulation, which will bolster your confidence as a future marketing professional in informing and/or taking business actions based on data. Note that this is a hands-on marketing course: As part of the racing simulation, you will compete in groups on different race tracks, after experimenting during practice laps to update the car setup. More specifically, you will analyze training data to map how track characteristics and weather conditions, together with the car setup, translate to lap times. You will then prepare for the race by deciding on the ideal car setup. You can also experiment by taking the car around the track. This will allow you to devise the race strategy: When to pit and which tyres to equip. During the live race, you will learn from your rivals’ mistakes as well as your own, and use the feedback to improve. |
| Lernziele | At the end of the course, you will be able to generate decision-relevant insights for informing and/or taking business actions. Using the various functionalities of the statistical computing software R, you will be able to • Manipulate and visualize data. • Apply machine learning. • Report insights. |
| Literatur | • Provost, F. and T. Fawcett (2013). Data Science for Business, O’Reilly. |
| Bemerkungen | Please submit a motivation email to andreas.lanz@unibas.ch by August 15. |
| Teilnahmevoraussetzungen | Payment of a one-time user fee for the racing simulation (CHF 30.-) and successful completion of the Marketing Analytics colloquium as well as of DataCamp’s “Machine Learning Fundamentals in R” |
| Anmeldung zur Lehrveranstaltung | Please submit a motivation email to andreas.lanz@unibas.ch by August 15. Eucor-Students and mobility students of other Swiss Universities or the FHNW also have to register at the University of Basel BEFORE the start of the course and receive their login data by post (e-mail address of the University of Basel). Processing time up to a week! Detailed information can be found here: https://www.unibas.ch/de/Studium/Mobilitaet.html Applies to everyone: enrollment = registration for the assessment! |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| täglich | Siehe Einzeltermine | ||
Einzeltermine
| Datum | Zeit | Raum |
|---|---|---|
| Montag 24.08.2026 | 08.15-17.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S17 HG.38 |
| Dienstag 25.08.2026 | 08.15-17.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S17 HG.38 |
| Mittwoch 26.08.2026 | 08.15-17.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S17 HG.38 |
| Module |
Modul: Business Field: Marketing (Masterstudium: Business and Technology) Modul: Business Field: Strategy and Organization (Masterstudium: Business and Technology) Modul: Core Courses in Marketing and Strategic Management (Masterstudium: Wirtschaftswissenschaften) Modul: Specific Electives in Business and Economics (Masterstudium: Wirtschaftswissenschaften) Modul: Specific Electives in Labor Economics, Human Resources and Organization (Masterstudium: Wirtschaftswissenschaften) Modul: Specific Electives in Marketing and Strategic Management (Masterstudium: Wirtschaftswissenschaften) |
| Prüfung | Leistungsnachweis |
| Hinweise zur Prüfung | Two debrief presentations, namely on the first and third day, rank in the championship, and (intra-group) peer evaluation counting 25%, 25%, 25%, and 25% toward the final grade (attendance and participation is a must!) |
| An-/Abmeldung zur Prüfung | An- und Abmelden: Dozierende |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,1 |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch |
| Anbietende Organisationseinheit | Wirtschaftswissenschaftliche Fakultät / WWZ |