Course Organization

14 setembro 2020, 12:59 • Cláudia Antunes

Welcome to the Data Science course!

There are two lectures and one lab per week. 

LECTURES
All lectures are remote through ZOOM, and there is just one lesson simultaneously for Alameda and Tagus students, on Mondays at 11 o'clock and Thursdays at 12:30.

Each lesson starts 30 minutes after the hour. Those first 30 minutes should be used to watch the videos scheduled for the lesson. The other 60 minutes will be used to discuss case studies, exploring the topics addressed on the videos.

Classes on Mondays at 14:00 and Tuesdays 12:30 will be used to give extra support for the project, to discuss individually with each group what to explore in the project.

LABS
Labs are optional, and will be only used for evaluating the project progress. So, only students that opt to be graded on labs should attend. There is no topic or exercise solved on them. 

Evaluation will be made EVERY week. 

All students from each group should be present in the labs (in the room or remotely via ZOOM). Only students present will be graded. 

Teacher will give 10 minutes of attention to each group, evaluating their progress and helping if needed. Due to the nature of support, it will be done through ZOOM, both for students in  the room or remotely.

Each group aiming to be present in the room, should came to the lab 5 minutes before its schedule, in order to have at most 6 students inside room at the same time. Groups will be attended according to their group number (the schedule will be published).

Groups can be composed by any 3 students, independently of their shift, including Alameda and Tagus. However, only students of the same shift may be on the room simultaneously. Of course some of the students may be online.

NEW - Enrolment

Enrolment in the Labs is mandatory,  and will be open on September 21st at 17:00. There is a limit of 9 teams per lab. Each team has to have 3 students. The exception are Trabalhadores-Estudantes, who can work alone or in teams of 2 - send me an email if this is your case, since you would not be able to enrol your team.

If you don't have a team yet, see the post "Labs enrolment" in the Data Science course forum!

Good work!