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Data Scientist in Python

Master the skills you need to pass the Data Scientist in Python certification and prepare yourself for success in the field of data science. Throughout this track, you will focus on using Python for data science, starting with the basics and progressing to more advanced topics such as machine learning. You’ll cover a broad range of areas, including data manipulation, visualization, and analysis, using popular Python libraries such as pandas, Seaborn, Matplotlib, and scikit-learn. As you progress, you’ll work through interactive exercises using real-world datasets to help you test your abilities and develop your skills. These examples will help you explore various statistical and machine learning techniques, including hypothesis testing and predictive modeling. You’ll also gain an understanding of package development, data preprocessing, SQL for relational databases, Git for data science projects, and more. Complete this track to gain the knowledge and experience necessary to confidently pass the Data Scientist in Python certification and thrive as a data scientist.

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1
Python
Intermediate Importing Data in Python

Improve your Python data importing skills and learn to work with web and API data.

2 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist

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Instructors

  • Hugo Bowne-Anderson Headshot
    Hugo Bowne-AndersonData ScientistSee Hugo Bowne-Anderson's Portfolio
  • James Chapman Headshot
  • James Fulton Headshot
  • Karolis Urbonas Headshot

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