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Exploratory Data Analysis and Visualization with Python

90-800

Units: 6

Description

This course covers the fundamentals of exploratory data analysis (EDA) and data visualization with Python. Through exploratory data analysis, students will learn how to perform an initial analysis on data, how to ask questions to their data, discover patterns and anomalies. This course will focus on asking questions to build data stories, applying statistical concepts to analyze data, and producing effective visualizations.

Learning Outcomes

  • Understand and apply statistical concepts to analyze data.
  • Be able to produce, comprehend and run Python code for commonly used EDA practices and data visualization techniques.
  • Understand and produce effective data visualizations that allow for data storytelling, such as data exploration and hypothesis testing.
  • Understand good data practices and apply them to different types of real-world data.

Prerequisites Description

  • 90-819 Intermediate Programming with Python
  • A statistics course such as 90-707, 90-711, or 95-796

Syllabus