Data, Data Storage, Data Collection

Data is the foundation of intelligent systems and decision-making processes. Understanding how to work with data, from its collection to its use for decision making, is central to modern data-driven applications. This course introduces students to the full data lifecycle. It explores how to collect, clean, store, and analyze data, before discussing how to communicate the findings.

Content will be made accessible here and on ESSEC’s educational platform.

Session 1: Introduction to Data and the Data Lifecycle

• Lecture slides.
• Exercise sheet.
• Solution of the exercise sheet.
• Lab: the archive contains a Jupyter Notebook alongside a fallbacks dataset. The lab is intended as a refresher on pandas while putting the core concepts from the lecture into practice.
• Solution of the lab.
• Project guidelines: slides and written instructions.

Session 2: Representation in Data Collection

• Lecture slides.
• Exercise sheet.
• Solution of the exercise sheet.

Session 3: Generating and Measuring Data

• Lecture slides.
• Exercise sheet.
• Solution of the exercise sheet.
• Lab.
• Solution of the lab.

Previous Version

The previous version of this course was taught in 2025. The content is still available here but note that some of the content has been updated for the 2026 version.