This is the third of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn how to find the story within data and tell that story in a compelling way. You'll discover how data professionals use storytelling to better understand their data and communicate key insights to teammates and stakeholders. You'll also practice exploratory data analysis and learn how to create effective data visualizations.
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Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you build your data analytics skills to prepare for your career.
Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.
By the end of this course, you will:
-Use Python tools to examine raw data structure and format
-Select relevant Python libraries to clean raw data
-Demonstrate how to transform categorical data into numerical data with Python
-Utilize input validation skills to validate a dataset with Python
-Identify techniques for creating accessible data visualizations with Tableau
-Determine decisions about missing data and outliers
-Structure and organize data by manipulating date strings
This course is part of the Google Advanced Data Analytics Professional Certificate.
Syllabus
WEEK 1
Find and share stories using data
You’ll learn how to find the stories within data and share them with your audience. You’ll learn about the methods and benefits of data cleaning and how it can help you discover those stories. You’ll also go over the steps of the EDA process and learn how EDA can help you quickly understand data. Finally, you'll explore different ways to visualize data to communicate key insights.
WEEK 2
Explore raw data
Finding stories in data using EDA is all about organizing and interpreting raw data. Python can help you do this quickly and effectively. You’ll learn how to use Python to perform the EDA practices of discovering and sculpting.
WEEK 3
Clean your data
You’ll explore three more EDA practices: cleaning, joining, and validating. You'll discover the importance of these practices for data analysis, and you’ll use Python to clean, validate, and join data.
WEEK 4
Data visualizations and presentations
You’ll practice creating and presenting data stories in an ethical, accessible, and professional way. You'll also explore advanced data visualization techniques in Tableau.
WEEK 5
Course 3 end-of-course project
In this end-of-course project, you’ll practice using Python to perform EDA on a workplace scenario dataset. Then, you'll use Python and Tableau to visualize the data.
