Learning Objectives
It’s hands on. 80% practical, 20% theory.
Program in python and work with Git & GitHub repositories;
Understand the data science processes (data exploration, preprocessing, building a ML model, performance indicators and error metrics, model optimization);
Smart visualization to transform data into information;
Think critically about data and draw conclusions based on your analysis;
Grasp an understanding of the most commonly used tools in the Industry and learn how to use them to support your needs.