Introduction
Foundations Data, Data, Everywhere
Foundations
The Six Phases of Data Analysis
Ask Questions to Make Data-Driven Decisions
Different Problem Types
Mathematical thinking
Using the Spreadsheet
Working with Stakeholders (Optional)
Prepare Data for Exploration
Data Types and Structures
Source of Data
Forms of Data
Organizing and Protecting Data
Networking Skills (Optional)
Process Data from Dirty to Clean
Data Integrity
Using Statistics
Ways to Clean Data
Using SQL to Clean Data
Reporting and Validating Clean Data
Build Your Resume (Optional)
Analyze Data to Answer Questions
Organizing Data
Converting and Formatting Data
Data Aggregation
Data Calculation
Share Data Through the Art of Visualization
Visualizing Data
Present the Data
Data Analysis with R Programming
Introduction to Programming Languages
Introduction to R
Clean Data Using R
Data Visualization Using R
R Documentation
Google Data Analytics Capstone Complete a Case Study
Published with GitBook
Working with Stakeholders (Optional)
Working with Stakeholders
(Optional)
Communication skills
Agenda
: A list of scheduled appointments.
Conflict Resolution
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