This is a 15-hour online course that exposes you to state-of-the-art tools employed in data science. The course is taught with a hands-on approach via Jupyter notebooks. The course is composed of three units that guide participants through the process of converting raw data into actionable insights:
Data handling and visualization
Supervised learning: 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
Unsupervised learning: participants are introduced to the main concepts and tools for dealing with unsupervised learning problems, such as clustering algorithms and Principal Components Analysis
Become familiar with the most important techniques used by data scientists
Classes will consist of rigorous training of the topics together with practical sessions to learn how to deploy these techniques to real data sets. Built around Jupyter Notebooks, this course offers participants the opportunity to improve their programming skills in both Python and R, the most widely used programming languages in data science.
After successful completion of this course, you will have:
Worked with and extracted valuable insights from real data
Improved programming skills in two of the most used programming languages in data science
Skills to understand some of the key methods, as well as their limitations, used by data scientists
Gained practical experience in applying these methods to large and heterogeneous data
Learnt how to work with large data sets
Get up to speed on the latest developments in data science in a short time
INTENSIVE COURSE
Foundations of Data Science
Mar 6-8, 2024 | FACE-TO-FACE OR ONLINE
NEXT EDITION: TBA
Applications will open soon!
ONLINE
FACE-TO-FACE
Regular Fee
1300 €
1475 €
Reduced Fee
775 €
850 €
10% early-bird discount applies to payments made on or before February 6, 2024 at 23:59 (CET)