Data Mining

This course offers a comprehensive introduction to Data Mining, a discipline aimed at extracting useful knowledge, trends, and hidden patterns from large volumes of raw data. The course combines theoretical foundations (statistics, machine learning, databases) with practical applications through tools and real-world case studies.

This course is dedicated to 4th-year engineering students specializing in Software Engineering.


 Course Objectives

By the end of this course, learners will be able to:

  1. Understand the fundamental concepts of data mining and its role in the knowledge discovery process
  2. Master the main techniques of preprocessing, classification, clustering, and association rule mining
  3. Select the most suitable algorithm based on the nature of the problem and the available data
  4. Implement these techniques using dedicated tools and programming languages (Python, R, etc.)
  5. Evaluate the performance and relevance of the resulting models using appropriate metrics
  6. Apply these skills to real-world problems across various domains (marketing, finance, healthcare, e-commerce, etc.)
  7. Develop critical thinking regarding the results obtained, particularly on issues of bias, data quality, and ethics in data exploitatiion