General objective

Based on the principles of the new emerging data science, study the architectures and environments that ease the deployment of solutions. Teach how to apply data science method and techniques for concrete modelling and prediction experiments running on top of target architectures.

Learning outcomes

At the end of the course the student will be able to deploy Data Science experiments on target environments, exhibiting the pipelines behind and execution strategies to be considered for running experiments at scale. The student will:

• Understand theoretically and technically the steps of a general data science process.
• Apply tools for executing data science pipelines.
• Learn how to make decisions on the data analytics techniques to apply according to the data properties and the analytics objective.
• Know how to define strategies to scale analytics solutions for dealing with Big Data settings using different computing resources.