Data Science Methodology

Coursera MOOC / Non-credit USD 39
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Data Science Methodology

About this course

If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. In this course, you will learn and then apply this methodology that you can use to tackle any Data Science scenario. You’ll explore two notable data science methodologies, Foundational Data Science Methodology, and the six-stage CRISP-DM data science methodology, and learn how to apply these data science methodologies. Most established data scientists follow these or similar methodologies for solving data science problems. Begin by learning about forming the business/research problem Learn how data scientists obtain, prepare, and analyze data. Discover how applying data science methodology practices helps ensure that the data used for problem-solving is relevant and properly manipulated to address the question. Next, learn about building the data model, deploying that model, data storytelling, and obtaining feedback You’ll think like a data scientist and develop your data science methodology skills using a real-world inspired scenario through progressive labs hosted within Jupyter Notebooks and using Python.

What you'll learn

  • understanding foundational data science methodologies
  • applying the six-stage CRISP-DM methodology
  • forming and analyzing business/research problems
  • obtaining and preparing data for analysis
  • building and deploying data models
  • presenting data insights through storytelling

Skills you'll gain

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