Checking date: 12/04/2023

Course: 2023/2024

Data Analitics
Bachelor in Robotics Engineering (Plan: 478 - Estudio: 381)

Coordinating teacher: NOGALES MARTIN, FCO. JAVIER

Department assigned to the subject: Statistics Department

Type: Electives
ECTS Credits: 3.0 ECTS


Requirements (Subjects that are assumed to be known)
Linear algebra Probability and Data Analysis Introduction to Statistical Modeling
Become familiar with different analytical tools, based on data, to make business decisions Capacity to develop skills to analyze and find relationships between many variables/features Know how to evaluate supervised-learning models Develop skills to classify observations based on probabilistic learning and machine learning tools Handle the R language for statistical-learning tools
Skills and learning outcomes
Description of contents: programme
1. Introduction to the statistical learning 2. Evaluation of learning methods 3. Unsupervised learning 3a. Clustering 3b. Dimension reduction 4. Probabilistic learning 4a. Statistical classification 4b. Regression and prediction 5. Case studies
Learning activities and methodology
Theory (3 ECTS), Practice (3 ECTS). 50% lectures with teaching materials available on the Web. The other 50% practical sessions (computer labs).
Assessment System
  • % end-of-term-examination 50
  • % of continuous assessment (assigments, laboratory, practicals...) 50
Calendar of Continuous assessment

The course syllabus may change due academic events or other reasons.

More information: Aula Global