Data culture is essential in the environment of digitalisation and digital transformation. Therefore, the data science environment provides a set of tools and techniques for gathering information from the data to help us in decision making. This course explores predictive (supervised) techniques in ML as tools to build predictive models from the information contained in databases. We will review the main classification algorithms and implement specific examples with Python to end up with an idea of the possibilities of this type of algorithms which are part of the field of artificial intelligence.
The course is taught by Dr. David Roche.
Prerequisites & admissions
Registration from 1 March to 30 May 2023. Admission by order of registration (40 places).
Description
Panel data analysis is a very widely used statistical method in studying relationship between variables. It is used in social sciences to analyse two-dimensional (typically cross-sectional and longitudinal) panels. Nowadays many data scientists use R while analysing data because it contains a comprehensive library and different packages that contain many useful functions for statistical calculations and random number generation. R provides a flexible analysis toolkit where all the standard statistical techniques are built in.
Dr Yaghoub Abdi will give the course.
Prerequisites & admissions
Registration from 1 March to 30 May 2023. Admission by order of registration (40 places).