Over the last decade the world has witnessed a surge in the amount of data available for decision making. The availability of large and complex datasets has lead to the widespread use of machine learning methods to extract and process information in both the academia and industry.

The Barcelona School of Economics Foundations of Data Science Intensive Course provides participants with a practically oriented overview of the state-of-the-art tools employed in data science tasks.

The course is composed of three units that guide participants through the process of converting raw data into actionable insights:

• First, participants are introduced to topics in data handling and visualization.
• Second, the course covers some of the most relevant Supervised Learning tools, ranging from linear models such as LASSO, Ridge and Elastic Net to nonlinear models, such as Decision Trees, Random Forests and Boosting.
• Finally, participants are introduced to the main concepts and tools for dealing with unsupervised learning problems, such as clustering algorithms and Principal Components Analysis.

Built around Jupyter Notebooks, the course offers participants the opportunity to improve their programming skills in both Python and R, the most widely used programming languages in Data Science.

CODING KNOWLEDGE REQUIRED

Those with no experience in either R or Python, or who haven’t used either for a while, must also register separately for the course Coding Bootcamp in Python and R, which will be conducted online on Friday, April 29.