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Self-Paced Course

Data Science in Python: Data Prep & EDA

Master the foundations of Python for data science, including project scoping, data gathering & cleaning, EDA,feature engineering, and more.

Course Hours14.5 hours
Skills Learned
Data Prep
Machine Learning
Data Analysis
Course Level

Course Description

This is a hands-on, project-based course designed to help you master the core building blocks of Python for data science.

We'll start by introducing the fields of data science and machine learning, discussing the difference between supervised and unsupervised learning, and reviewing the data science workflow we'll be using throughout the course.

From there we'll do a deep dive into the data prep & EDA steps of the workflow. You'll learn how to scope a data science project, use Pandas to gather data from multiple sources and handle common data cleaning issues, and perform exploratory data analysis using techniques like filtering, grouping, and visualizing data.

Throughout the course you'll play the role of a Jr. Data Scientist for Maven Music, a streaming service that’s been struggling with customer churn. Using the skills you learn throughout the course, you'll use Python to gather, clean, and explore the data to provide insights about their customers.

Last but not least, you'll practice preparing data for machine learning models by joining multiple tables, adjusting row granularity, and engineering useful fields and features.

If you're an aspiring data scientist looking for an introduction to the world of machine learning with Python, this is the course for you.



  • 8.5 hours on-demand video

  • 16 homework assignments

  • 7 quizzes

  • 2 projects (1 mid-course, 1 final)

  • 2 skills assessments (1 benchmark, 1 final)



  • Data analysts or BI experts looking to transition into a data science role

  • Python users who want to build the core skills required before applying for Machine Learning models

  • Anyone interested in learning one of the most popular open source programming languages in the world


  • Jupyter Notebooks (free download, we'll walk through the install)
  • Familiarity with base Python and Pandas is recommended, but not required

Start learning for FREE, no credit card required!

Every subscription includes access to the following course materials

  • Interactive Project files
  • Downloadable e-books
  • Graded quizzes and assessments
  • 1-on-1 Expert support
  • 100% satisfaction guarantee
  • Verified credentials & accredited badges
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