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Master Data Analysis with Python

Master Data Analysis with Python is a comprehensive course to learn data analysis and visualization in Python. There are over 850 pages of material, 500 exercises, 5 certification exams, multiple projects, detailed solutions, and 10 hours of video.

This course is divided into 13 parts:

  1. Intro to Pandas
  2. Selecting Subsets of Data
  3. Essential Series Commands
  4. Essential DataFrame Commands
  5. Data Types
  6. Grouping Data
  7. Time Series
  8. Regular Expressions
  9. Tidy Data
  10. Joining Data
  11. Fundamentals of SQL
  12. Visualization with matplotlib
  13. Visualization with pandas and seaborn

For a more detailed description of each topic, visit the main Master Data Analysis with Python page.

 

Get Master Machine Learning with Python for Free!

For a limited time, you'll get access to the latest draft of Master Machine Learning with Python for free! This book contains 25 chapters and 225 pages of material and currently being updated. Once the book is complete, it will be sold separately.

Become an Expert

Many other courses use poor practices to teach the data science libraries such as pandas, matplotlib, and seaborn. With Master Data Analysis with Python, you will be given the absolute best practices to use the libraries that massively increase your efficiency. This text will rapidly help you become an expert.

100% Satisfaction Guaranteed or your Money Back

Worried about making the wrong purchase? Don't! Get a full refund if you aren't 100% satisfied with this course within 30 days.

All Access Pass!

Instead of purchasing each product separately, get lifetime access to all current and future products with the All Access Pass! for one low price.

About the Author

This course is taught by Ted Petrou, an expert at Python, data exploration and machine learning. Ted is the author of the highly rated text Pandas Cookbook. Ted has taught hundreds of students Python and data science during in-person classroom settings. He sees first hand exactly where students struggle and continually upgrades his material to minimize these struggles by providing simple and direct paths forward.

Ted is one of the foremost authorities on using the pandas library to do data analysis. His blog posts have totaled well over 1 million views. He is also a prolific contributor on Stack Overflow having answered over 400 questions.

Ted holds a master's degree in statistics from Rice University and is the author of Master the Fundamentals of Python and Master Data Analysis with Python.

What your purchase includes

You are purchasing access to the following:

  • 70+ Jupyter Notebook where you can read the text, complete exercises, and add notes.
  • 850+ page PDF of the text allowing you to search for specific content or read when not online.
  • 10 hours of videos covering the content in the notebooks
  • 5 challenging certification exams that are graded. Upon passing the exams, a certificate of completion is given
  • Access to an 6-week live online cohort-based course
  • Access to the Master Machine Learning with Python course
  • Access to a Slack workspace where you can ask questions about the course

Prerequisites

Master Data Analysis assumes you already have a solid understanding of the fundamentals of Python. If you do not, you should master these fundamentals first. Master the Fundamentals of Python provides the necessary prerequisite knowledge.

This book assumes no knowledge of any of the Python data science libraries. Each part progresses slowly and thoroughly beginning with the basics. Advanced topics are covered towards the last chapters in each part.

Videos Lessons

More than 10 hours of video lessons are available for the first six parts of the course. Videos for the other parts are being created now.

What People Are Saying:

In my opinion what distinguishes you from everyone is your deep understanding of Python and Pandas. I follow lot of people on twitter, linkedin, Medium who share tips/tricks/codes on Python, Pandas, scikit-learn but no one comes close to you when writing efficient code and explaining the finer nuances.