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Module 2
Workload
45h
Disciplines
3
Full program
360h
Descriptive Data Analysis
Module focused on reading, organizing, and analytically exploring data.
The second module deepens analytical reading of data, enabling students to describe, visualize, prepare, and synthesize complex datasets in order to generate insight, understanding, and value before predictive modeling.
Module disciplines
01
15h
Descriptive Statistics and Data Visualization
Professor Alexandre Magno
Syllabus
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Variable types. Chart types. Fundamentals of visual perception. Quantitative relationships. Visual patterns. Analytical interaction techniques. Dashboard construction. Color theory. How to tell stories with data. Visualization evaluation.
02
15h
Dimensionality Reduction Techniques
Professor Profª. Drª. Helen de Cássia Lima
Syllabus
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Data types. Data quality. Preprocessing. Similarity and dissimilarity measures. File formats and data storage. Data cleaning and preparation. Data organization. Aggregation and grouping operations. Dimensionality reduction. Feature selection.
03
15h
Unsupervised Learning
Professor Alexandre Magno
Syllabus
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Techniques for summarizing multivariate data: principal component analysis, factor analysis, and discriminant analysis. Multivariate analysis of variance. Cluster analysis: K-means, DBSCAN, Gaussian Mixture Models, and Hierarchical Clustering.