-
Presentation
Presentation
Acquire and develop skills to represent and interpret reality through data and to use artificial intelligence methods to identify patterns and make predictions.
-
Class from course
Class from course
-
Degree | Semesters | ECTS
Degree | Semesters | ECTS
Master Degree | Semestral | 6
-
Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
-
Code
Code
ULHT6606-23869
-
Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
-
Professional Internship
Professional Internship
Não
-
Syllabus
Syllabus
- Data preparation
- Database modeling
- Business intelligence
- Descriptive statistics
- Visualization
- Python
- CRISP-DM
- Classification
- Prediction
- Cluster analysis
- Neural networks
-
Objectives
Objectives
Current times are characterized by an exponential growth in the volume, variety and velocity of data production. The curricular unit of Data Science aims to teach students, with the support of case studies and software, main methodologies, methods, techniques and tools that underpin the preparation, structuring, description, analysis, inference and visualization of data to extract knowledge, detect patterns and support decision-making. It is intended that students develop skills in identifying problems that can be solved using data science, in describing data, in structuring problems through descriptive and predictive models, in the use of data analysis tools and in the interpretation of the results obtained after applying statistical and artificial intelligence methods.
-
Teaching methodologies and assessment
Teaching methodologies and assessment
State-of-the-art software and hands-on application of the syllabus to solve a real-world case.
-
References
References
-
Moreira, JM, Carvalho, A, Horváth, T (2018) A general introduction to data analytics. Hoboken: Wiley
-
Igual, L, Seguí, S (2017) Introduction to Data Science - A Python Approach to Concepts, Techniques and Applications. Springer
-
-
Office Hours
Office Hours
-
Mobility
Mobility
No