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Exploratory Data Analysis (EDA) with Python,
Go Beyond the Numbers: Translate Data into Insights,
Google Advanced Data Analytics Course 3

for downloading the course material see 1st comment


**Time stamps**

Module 1: Find and Share Stories Using Data

00:00:00 Introduction to Course 3
00:04:59 Robb_ Obstacles and achievements
00:08:46 Welcome to module 1
00:09:48 Find stories using the six exploratory data analysis practices
00:19:22 Benj_ Data science and storytelling
00:22:06 Combine PACE and EDA practices
00:28:37 PACE with data visualizations
00:34:06 Wrap-up

Module 2: Explore Raw Data

00:37:00 Welcome to module 2
00:40:05 Yaser_ Understand data to drive value
00:42:09 Where the data comes from
00:52:44 EDA using basic data functions with Python
01:02:53 Discover what is missing from your dataset
01:08:52 Date string manipulations with Python
01:22:46 Use structuring methods to establish order in your dataset
01:27:45 EDA structuring with Python
01:44:10 Wrap-up

Module 3: Clean your Data

01:47:32 Welcome to module 3
01:51:24 Methods for handling missing data
01:59:47 Work with missing data in a Python notebook
02:12:09 Remy_ A day in the life of a data professional
02:14:43 Account for outliers
02:20:45 Identify and deal with outliers in Python
02:34:15 Sort numbers versus names
02:39:02 Label encoding in Python
02:47:59 The value of input validation
02:55:29 Input validation with Python
03:03:41 Wrap-up

Module 4: Data Visualizations and Presentations

03:05:57 Welcome to module 4
03:08:44 The visualization life cycle
03:13:55 Work with Tableau, Part 1
03:20:41 Work with Tableau, Part 2
03:28:11 Drew_ Explore the possibilities of data
03:28:47 Craft compelling stories with Tableau
03:37:32 Present like a pro with Tableau
03:43:59 Wrap-up

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