| Code |
16513
|
| Year |
1
|
| Semester |
S2
|
| ECTS Credits |
6
|
| Workload |
TP(60H)
|
| Scientific area |
Economics
|
|
Entry requirements |
Not applicable.
|
|
Mode of delivery |
Face-to-face
|
|
Work placements |
Not applicable
|
|
Learning outcomes |
1. Introduce students to information search and processing techniques;
2. Enable students to perceive the fundamental characteristics of economic and business variables;
3. Enable students to use spreadsheets in an advanced way for data presentation and transformation;
4. Enable students to display results using large volumes of data.
|
|
Syllabus |
1. Tools to support the economy: fundamental concepts and typologies;
2. Data collection;
3. Data preparation;
4. Data analysis methods and techniques;
5. Presentation of results.
|
|
Main Bibliography |
Guerrero, Hector,. 2019. Excel Data Analysis: modeling and simulation, Springer, 2nd edition.
Provost, Foster e Fawcett, Tom,. 2013. Data Science for Business: what you need to know about data mining and data-analytic thinking, 1st edition.
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Teaching Methodologies and Assessment Criteria |
The students' classification corresponds to the weighting of three assessment moments:
• First exam 20% - 21 March
• Second exam 25% - 29 April
• Third exam 25% - DGE Evaluation Week
• Project 30%
Project Delivery 20% - 15 April
Presentation 10% – 17 April
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|
Language |
Portuguese. Tutorial support is available in English.
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