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Detalhe da Disciplina
Curso: Pós-Graduação em Análise e Gestão de Informação
Unidade curricular: Métodos Descritivos de Data Mining
Semestre: Outono
Número de créditos: 7,5
Número de horas de aula por semana: 12.00
Objetivos da unidade curricular:

Data Mining uses interdisciplinary techniques, such as statistics, data visualization, database systems, and machine learning to identify original, useful, and understandable patterns in data.
This course will familiarize students with Data Mining applications and Data Mining projects' lifecycle. Students will learn techniques for understanding and preparing data before building descriptive models, such as clustering or association rules (e.g., market basket analysis).

Requisitos de frequência:

Familiarity with the main theme of the course is not required. But it is highly recommended that the students have knowledge of Inferential Statistics as well as good skills as a computer user.

Students without previous training or experience with Python should complete the two following Datacamp online courses before the third week of this course (first practical class):  Introduction to Python and Intermediate Python. Students who wish could also complete, optionally, the course Data manipulation with pandas. The instructor will provide information on how to have free access to the Datacamp platform.

Língua de ensino: Português. Em caso de existirem alunos ou professores estrangeiros, as aulas serão dadas em Inglês.