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Data-Driven Innovation

EI7480Examination Performance5 ECTSEnglishwinter semesterDepartment Computer Engineering
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You learn how data-driven innovations are conceived and implemented. By the end you can identify user needs, derive suitable data opportunities, classify the necessary data processing steps along the Data Value Chain, and outline data-based business models as well as their integration into the ecosystem.

What you will be able to do

  • Analyze user/customer needs and align them with data opportunities
  • Systematically acquire and manage data sources
  • Understand processing steps along the Data Value Chain
  • Apply simple data analysis and modeling approaches
  • Scope and position data-driven business models
  • Evaluate ecosystem/network dynamics

What the module consists of

  • VorlesungConveying the conceptual steps and theoretical foundations
  • Übungen / ArbeitsgruppenPractical development of methods and interim presentations
  • SemestersprojektTeamwork to apply the content to a concrete innovation project
  • HomeworksIndividual tasks to reinforce problem-solving abilities

Teaching method

  • Frontalunterricht (Beamer, Tafel)Introduction to concepts and theoretical foundations
  • Diskussionen und KleingruppenarbeitDeepening and practical application of methods
  • Praktische Übungen und BeispieleAcquisition of concrete skills in data preparation and modeling
  • Semesterprojekt mit PräsentationenApplication, teamwork and communication of results
  • Storytelling / Video-ProduktionIllustration and communication of practical examples

Dates

LectureData Driven Innovation3 groups to choose from

  • ATue09:00–17:00Z995, Seminarraum (0509.Z1.995)
    2× · 13.10.–24.11.
    • 13.10.
    • 24.11.
  • BFri09:00–17:00Z995, Seminarraum (0509.Z1.995)once on 09.10.
  • CSat09:00–17:00Z995, Seminarraum (0509.Z1.995)once on 10.10.

From the current semester, not binding. You attend one of several groups; the timetable automatically suggests the one with the fewest clashes.

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Official page in TUMonline · Details are not binding.