Objectives of Programme's Learning Outcomes

• Manage research, development and innovation.
• Understand unprecedented problems in computer science and its applications.
• Master communication techniques.
• Communicate, both orally and in writing, their findings, original proposals, knowledge and underlying principles, in a clear, structured and justified manner.
• Develop and integrate a high degree of autonomy.
• Aquire new knowledge independently.
• Apply scientific methodology.
• Critically reflect on the impact of IT in general, and on the contribution to projects.
• Demonstrate thoroughness, independence, creativity, intellectual honesty, and ethical values.

Learning Outcomes of UE

Study of statistical/machine learning algorithms for supervised and unsupervised problems. Study of linear and non-linear models for regression, classification, clustering and dimensionality reduction.

UE Content: description and pedagogical relevance

See the single learning activity.
 

Prior Experience

Basics of Probability and Statistics
Basics of Matrix Algebra
Basics of Non-linear optimization