Python Data Science: Data Prep & EDA with Python

Learn Python + Pandas for data cleaning, profiling & EDA, and prep data for machine learning & data science with Python

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

We'll start by introducing the fields of data science and machine learning, discussing the difference between supervised and unsupervised learning, and reviewing the Python 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 Python and Pandas to gather data from multiple sources and handle common data cleaning issues, and perform exploratory data analysis (EDA) 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 data science and machine learning models by joining multiple tables, adjusting row granularity, and engineering useful fields and features.

COURSE OUTLINE:

• Intro to Data Science & Machine Learning

  • Introduce the field of data science, review essential skills, and introduce each phase of the data science workflow

  
  

• Scoping a Project

  • Review the process of scoping a data science project, including brainstorming problems and solutions, choosing techniques, and setting clear goals

  
  

• Gathering Data

  • Read flat files into a Pandas DataFrame in Python, and review common data sources & formats, including Excel spreadsheets and SQL databases

    
    

• Cleaning Data

  • Identify and convert data types, find and fix common data quality issues like missing values, duplicates, and outliers, and create new columns for analysis

  
  

• Exploratory Data Analysis (EDA)

  • Explore datasets to discover insights by sorting, filtering, and grouping data, then visualize it using common chart types like scatterplots & histograms

  
  

• MID-COURSE PROJECT

  • Put your skills to the test by cleaning, exploring, and visualizing data from a brand-new data set containing Rotten Tomatoes movie ratings

  
  

• Preparing for Modeling

  • Structure your data so that it’s ready for machine learning models by creating a numeric, non-null table and engineering new features

  
  

• FINAL COURSE PROJECT

  • Apply all the skills learned throughout the course by gathering, cleaning, exploring, and preparing multiple data sets for Maven Music

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Ready to dive in? Join today and get immediate, LIFETIME access to the following:

• 8.5 hours of high-quality video

• 16 homework assignments

• 7 quizzes

• 2 projects (1 mid-course, 1 final)

• Data Science in Python: Data Prep & EDA ebook (190+ pages)

• Downloadable project files & solutions

• Expert support and Q&A forum

• 30-day Udemy satisfaction guarantee

If you're an aspiring data scientist or business intelligence professional looking for an introduction to the world of machine learning and data science with Python and Pandas, this is the course for you.

Happy learning!

-Alice Zhao (Python Expert & Data Science Instructor, Maven Analytics)

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Looking for our full business intelligence stack? Search for "Maven Analytics" to browse our full course library, including Excel, Power BI, MySQL, Tableau and Machine Learning courses!

See why our courses are among the TOP-RATED on Udemy:

"Some of the BEST courses I've ever taken. I've studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I've seen!" Russ C.

"This is my fourth course from Maven Analytics and my fourth 5-star review, so I'm running out of things to say. I wish Maven was in my life earlier!" Tatsiana M.

"Maven Analytics should become the new standard for all courses taught on Udemy!" Jonah M.