Teaching plan for the course unit

 

 

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General information

 

Course unit name: Introduction to Machine Learning

Course unit code: 569389

Academic year: 2021-2022

Coordinator: Maria Salamo Llorente

Department: Department of Mathematics and Computer Science

Credits: 5

Single program: S

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Estimated learning time

Total number of hours 125

 

Face-to-face and/or online activities

60

(Due to COVID-19 restrictions, we expect to have 50%-75% of in-person activities)

Independent learning

65

 

 

Teaching blocks

 

1. Unsupervised Learning

1.1. Introduction to unsupervised learning

1.2. Cluster analysis

1.3. Factor Analysis

1.4. Visualization

2. Supervised learning

2.1. A gentle introduction to supervised learning 

2.2. Lazy Learning

2.3. Feature selection 

2.4. Model Selection

2.5. Support Vector Machine

2.6. Recommender Systems

 

 

Teaching methods and general organization

 

Teaching will follow a face-to-face (in-person), virtual (online), or mixed model according to the instructions of the competent authorities. In principle, we expect to follow the mixed teaching model for the 2021-2022 academic year.

* In case of in-person teaching:

The weekly schedule of in-person activities is distributed in two hours of theory class and one hour of practical sessions. 

* In case of mixed teaching required by the health situation (this is the expected model):

If the health situation allows it and the necessary conditions are met, we expect to have between 50% and 70% of in-person activities. In general, when having an occupancy rate of 50%, students will attend in-person for a week and will follow class on streaming for the following week.

* In case on-line teaching is required by the health situation:

The time ranges of mixed teaching are maintained but all teaching will be carried out in an online format, prioritizing synchronous sessions for the subject dynamization.

As far as possible, the gender perspective will be incorporated in the development of the subject. In addition, teachers will be attentive to those specific gender needs that students may arise, such as being able to choose a partner of the same gender  if group work is carried out or being able to pose challenges against the gender gap.

 

 

Official assessment of learning outcomes

 

Depending on the health situation, evaluable activities can be face-to-face tests, synchronous online tests, or work delivery.

 

Examination-based assessment

Depending on the health situation, evaluable activities can be face-to-face tests, synchronous online tests, or work delivery.