The SAS introduces essential theoretical tools and Python programming techniques for data mining and analysis, seamlessly integrating theoretical insights with practical, hands-on sessions. This program also prepares students for more advanced studies in machine learning and deep learning. It is designed to accommodate participants with no prior knowledge of machine learning, ensuring accessibility and a foundational understanding for all attendees.

OBJECTIVES

Develop skills for data manipulation, visualization, and analysis in Python

Develop skills on multivariate analysis and clustering

Preparation for advanced machine learning course

PREREQUISITES

Programming knowledge

Basic knowledge of Python (optional but beneficial)

PROGRAM

Introduction to Python

Python tools for data management and analysis (pandas, numpy).

Introduction to data mining and specialised libraries (e.g., scikit-learn, SciPy)

Data visualisation and use of specialised Python libraries (e.g. matplotlib)

Descriptive statistics (mean, variance, z-score, histograms, etc.)

Data preparation (handling missing data, normalisation, handling outliers, etc.)

Multivariate analysis

Clustering