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Orientation: Data Driven Supply Chain Management

By University of Groningen

Type of course:

Digital learning, Lesson

Language:

EN

Duration:

5 minutes

Proficiency:

Beginner

Target:

Manager, Professionals, Workers

Have you ever felt overwhelmed trying to figure out where to start in an online course or how to make the most of it? In this lesson, we’ll ensure that doesn’t happen to you. This orientation is your roadmap for success in the course Data-Driven Supply Chain Management.

This lesson will:

  • Introduce the overall course structure, including its lessons, tasks, and assessments.
  • Help you choose the most relevant parts of the course to focus depending on your role (e.g., manager or technical learner).
  • Show you how to engage with the interactive examples, quizzes, and hands-on tasks.
  • Explain how to use resources like solution notebooks and the glossary effectively.

By the end of this lesson, you’ll feel confident about how to navigate the course and focus on the areas most valuable to your goals. Ready to get started? Let’s dive in!

About The Author

Dilek Dustegor is a Professor of Computing Science at the University of Groningen in the Netherlands. She is interested in bridging the gaps between research, development and implementation using AI and automation. She is pursuing research about modeling, design and analysis of large scale / networked systems using IoT and ML techniques, with a special interest in smart city applications. She is a seasoned educator, and loves using the newest educational technologies for an enhanced learning experience.


Learning outcomes

  1. By the end of this lesson, learners will be able to identify the different types of lessons (Info, Use-Case, Task, Test,) and define how each contributes to the overall learning experience.
  2. By the end of this lesson, learners will be able to determine which parts of the course are most relevant to their role (e.g., managerial or technical) and how to navigate the content based on their specific objectives.
  3. By the end of this lesson, learners will be able to engage with quizzes, interactive datasets, solution notebooks, and the glossary to maximize their understanding and practice throughout the course.

Topics

Automation and Sensoring, Automation and Robotics, Digital Transformation, Machine Learning

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Content created in 2024
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