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Course Description

Decision-makers generally do not use raw data to make decisions; they prefer data be summarized in easily understood formats that facilitate efficient decision-making. This course introduces data manipulation and visualization, both critical components of any data science project. This course introduces two commonly used data manipulation tools in the Python ecosystem: NumPy and Pandas. In addition, the Python ecosystem also includes a variety of data plotting packages such as Matplotlib, Seaborn, and Bokeh — each of which specialize in particular aspects of data visualization. This course will give you experience integrating NumPy, Pandas, and the plotting packages to create rich, interactive data visualizations that help drive efficient decision-making.

You are required to have completed the following courses or have equivalent experience before taking this course:

  • Constructing Expressions in Python
  • Writing Custom Python Functions, Classes, and Workflows
  • Developing Data Science Applications

Faculty Author

Chris Myers

Benefits to the Learner

  • Manipulate data arrays using NumPy
  • Manipulate data tables using Pandas
  • Visualize data with Python

Target Audience

  • Data analysts and business analysts
  • Database managers
  • Technical and systems analysts
  • Programmers interested in data science
  • Marketers
  • Business managers

Applies Towards the Following Certificates

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Cornell Center for Advanced Computing
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