Python for Data Analysis (Master S1 Class)

Basic information

Description

This hands-on course is designed to strengthen students’ programming skills while equipping them with the essential tools and techniques needed to process and analyze large datasets, including extensive text corpora. Students will gain comprehensive expertise in Python’s data science ecosystem, with a primary focus on the pandas library—widely regarded as the cornerstone for data analysis in Python. The course will cover foundational concepts, such as data cleaning, manipulation, and exploration, as well as advanced techniques, including multi-indexing, group-by operations, and performance optimization for handling large-scale datasets.
In addition to pandas, the course will introduce students to key libraries for data visualization, including seaborn, plotly, and D3, enabling them to create compelling and insightful plots. Students will also gain practical experience with scikit-learn, one of the most popular libraries for machine learning. By the end of the course, participants will be equipped to tackle complex data analysis challenges, transforming raw data into actionable insights and effective visualizations.

 

Learning outcomes

On successful completion of this course, students should:

  • tackle complex data analysis challenges, transforming raw data into actionable insights and effective visualizations
  • have an advanced knowledge of the python ecosystem for data science