Financial Data Analysis

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Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

Covers the analysis of KMnO4 concentrations using data from a CSV file.

Explores data visualization techniques, design impact, and interactive applications for effective information communication.

Explores EMG signal processing techniques using Excel for data analysis and visualization.

Explores LabVIEW essentials, troubleshooting common issues, managing cache, and data visualization techniques.

Explores Matlab programming with scripts and functions, vectorization, and 2D graphics.

Explores data visualization principles, including chart navigation, histograms, scatter plots, box plots, and color usage.

Covers the practical use of QGIS for spatial data analysis and visualization, including georeferencing historical maps and manipulating vector data.

Explores techniques and applications of data visualization, emphasizing the importance of effective communication and unconventional examples.

Explores data manipulation, exploration, and visualization in data science projects using Python.

Covers PCA, finding directions of largest variance, data dimensionality reduction, and limitations of PCA.

Covers best practices and guidelines for big data, including data lakes, typical architecture, challenges, and technologies used to address them.

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