Data Understanding and Preparation for Data Science

One challenge in the data science lifecycle is understanding the problem or opportunity, the next challenge is acquiring, understanding, and preparing data for the modeling phase. This step in the data science process is estimated to take up to 50% of the time allotted for a data science project.

This 3-hour online course addresses how to translate the problem statement into data sources, explore the data for relationships and recognize patterns, identify the starting inputs for the model, preparing data, and validating it for the model fitting process.


You will learn to:

  • Review the data science project methodology
  • Understand data source identification
  • Evaluate data findings to determine and validate modeling techniques
  • Review feature selection techniques
  • Understand data preparation techniques
  • Plan for data pipelines
  • Understand data visualization techniques for data understanding and data preparation

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