Master Pandas for Data Analysis

Become an expert at the Pandas Python library for data analysis by passing weekly certification exams in this live, 6-week online course.

Register now for just $199!

Trusted Expert

Ted Petrou teaches all classes and has over 1,000 hours of live, in-person instruction experience. He is the author of numerous books including Master Data Analysis with Python and Pandas Cookbook. He is also the developer of multiple Python libraries.

Certification Exams

In this fast-paced course, we'll cover the entire Pandas library. Each week you'll take a challenging certification exam to prove your knowledge of the material covered. You'll have access to hundreds of other exercises and solutions to help you prepare for the exams.

Video Lessons

Every student will get access to approximately two hours of recorded video lessons each week that cover the contents of the course. You'll be expected to watch the videos to prepare for the live classes.

Course Description 

Before the course

  • Assignment - You will be given an assignment on how to use Jupyter Notebooks and write Markdown that is expected to be completed before the start of the course.
  • Private Slack Channel - Upon registration, you be given access to Ted's private Slack channel where you can directly communicate him and ask him questions about the course.

Week 1 - Intro to Pandas

  • pandas DataFrames - The pandas library is a popular and powerful library to analyze data. You will get introduced to the DataFrame, the main container of data with lots of functionality to analyze data.
  • Selecting subsets of data - One of the most common and basic data analysis tasks is to select a certain subset of the data. This could be particular rows, columns, or both rows and columns. There are unfortunately many ways to select subsets of data with pandas. We will cover the best and most efficient ways to do so.

Week 2 - Essential Pandas Commands

  • Series operations - The simplest analysis we can perform involves operating on a single column of data, the pandas Series. We learn how to call methods that aggregate, and return a single value, as well as those that do not aggregate and return more than a single value.
  • Entire DataFrame operations - After understanding how to operate on a single column of data, we move to operations that involve multiple columns in a DataFrame. Operating on multiple columns opens up the possibility of changing the direction of the operation. 

Week 3 - Grouping Data

  • Grouping - All the operations used above were applied to all values of a Series or DataFrame. You will learn how to split your data into groups based on the unique values of one or more columns. This 'grouping' allows you to run different calculations for independent groups within your data.
  • Pivot tables - Grouping data often results in a summary that is difficult for humans to read. You will learn how to create pivot tables to present your data in a format that is easier to interpret.

Week 4 - Time Series Analysis

  • Time Series - You will learn how to select specific time periods of data, sample time series data at evenly spaced intervals, operate over a rolling window of time, and group by any time period you desire.

Week 5 - Regular Expressions

  • Regular expressions -You will learn how to find patterns within text by learning regular expressions. This will allow you to extract information from text data.

Week 6 - Cleaning Data

  • Tidy data - Real-world data is messy and not immediately available for aggregation, visualization or machine learning. Identifying messy data and transforming it into tidy data provides a structure to data for making further analysis easier. 

 After the course

  • Stack Overflow question answering - One of the best ways to prove your expertise to others is to answer questions from Stack Overflow. You will be given directions on how to find and answer questions.
  • Lifetime access to material - You will always have access to the material and any updates to it after the course has completed. Ted upgrades and adds to his material on a regular basis.
  • Lifetime Slack access - You will have lifetime access to Slack allowing you to interact with Ted and all of the previous students.

Course Structure

There are several separate blocks of time you'll need to commit to in order to complete the course:

  • Weekly assignments - each week you will be assigned chapters to read, videos to watch, and exercises to complete. This self-study represents the bulk of the course time commitment.
  • Live online sessions - twice weekly, Ted will host an online live 90 minute session answering student questions.
  • Certification exams - each week, a challenging exam will need to be taken and passed.
  • Total time investment - altogether you'll need to allocate approximately 20 hours per week to complete all of the tasks. 

Target Student

The Master Pandas for Data Analysis course targets those who have little to no experience using Pandas for data analysis, but do understand the fundamentals of programming in Python. If you do not feel comfortable with basic Python, then this course is not for you. It's imperative that you have a deep desire to become an expert at pandas. 

About the Instructor

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 a simple and direct path 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. He is an enthusiastic instructor and dedicates his time to helping students at their desk during exercises to ensure understanding.

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

Former Student Sayantan Mitra

Hear Sayantan's experience taking the bootcamp and then transitioning to a teaching assistant.


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