Page Index - sj50179/Google-Data-Analytics-Professional-Certificate GitHub Wiki

166 page(s) in this GitHub Wiki:

• Home
• Welcome to my study note wiki for theGoogle Data Analytics Professional Certificate
• My Certificate URL
• 1. Foundations: Data, Data, Everywhere
• 2. Ask Questions to Make Data-Driven Decisions
• 3. Prepare Data for Exploration
• 4. Process Data from Dirty to Clean
• 5. Analyze Data to Answer Questions
• 6. Share Data Through the Art of Visualization
• 7. Data Analysis with R Programming
• 8. Complete a Case Study
• 1.1.1.Start the Program
• 1.1.2.Transforming data into insights
• 1.1.3.Quiz
• 1.1.3.Understanding the data ecosystem
• 1.1.4.Weekly challenge 1
• 1.1.Introducing data analytics
• 1.2.1.Embracing Data Analyst Skills
• 1.2.2.Thinking about Analytical Thinking
• 1.2.3.Thinking about the Outcomes
• 1.2.4.Weekly challenge 2
• 1.2.Thinking analytically
• 1.3.1.Following the data life cycle
• 1.3.2.Outlining the data analysis process
• 1.3.3.The data analysis toolbox
• 1.3.4.Weekly challenge 3
• 1.3.Exploring the wonderful world of data
• 1.4.1.Mastering spreadsheet basics
• 1.4.2.Learn about Structured Query Language(SQL)
• 1.4.3.Visualizing the data
• 1.4.4.Introducing Qwiklabs
• 1.4.5.Weekly challenge 4
• 1.4.Setting up a data toolbox
• 1.5.1.Learn about data analyst job opportunities
• 1.5.2.The importance of fair business decisions
• 1.5.3.Optional : Exploring your next job
• 1.5.4.Weekly challenge 5
• 1.5.Discovering data career possibilities
• 1.6.Course Challenge
• 2.1.1.Problem solving and effective questioning
• 2.1.2.Take action with data
• 2.1.3.Solve problems with data
• 2.1.4.Craft effective questions
• 2.1.5.Weekly challenge 1
• 2.1.Asking effective questions
• 2.2.1.Understand the power of data
• 2.2.2.Follow the evidence
• 2.2.3.Connecting the data dots
• 2.2.4.Weekly challenge 2
• 2.2.Making data driven decisions
• 2.3.1.Working with spreadsheets
• 2.3.2.Using formulas in spreadsheets
• 2.3.3.Using functions in spreadsheets
• 2.3.4.Save time with structured thinking
• 2.3.5.Weekly challenge 3
• 2.3.Learning spreadsheet basics
• 2.4.1.Balance team and stakeholder needs
• 2.4.2.Communication is key
• 2.4.3.Amazing teamwork
• 2.4.4.Weekly challenge 4
• 2.4.Always remember the stakeholder
• 2.5.Course challenge
• 3.1.1.Collecting Data
• 3.1.2.Difference between data formats and structes
• 3.1.3.Explore data types, fields, and values
• 3.1.4.Weekly challenge 1
• 3.1.Data types and data structures
• 3.2.1.Unbiased and objective data & Explore data credibility
• 3.2.2.Data ethics and privacy & Understanding open data
• 3.2.3.Weekly challenge 2
• 3.2.Bias, credibility, privacy, ethics, and access
• 3.3.1.Working with databases & Managing data with metadata
• 3.3.2.Accessing different data sources
• 3.3.3.1.Qwiklab: Sorting and Filtering (Cleaning Data)
• 3.3.3.2.Qwiklab: Introduction to BigQuery
• 3.3.3.Sorting and filtering & Working with large datasets in SQL
• 3.3.4.Weekly challenge 3
• 3.3.Databases: Where data lives
• 3.4.1.Effectively organize data
• 3.4.2.Securing data
• 3.4.3.Weekly challenge 4
• 3.4.Organizing and protecting your data
• 3.5.Course challenge
• 4.1.1.Data integrity and analytics objectives
• 4.1.2.Overcoming the challenges of insufficient data
• 4.1.3.Testing your data & Consider the margin of error
• 4.1.4.Weekly challenge 1
• 4.1.The importance of integrity
• 4.2.1.Data cleaning is a must & Begin cleaning data
• 4.2.2.1.Hands On Activity: Clean data with spreadsheet functions
• 4.2.2.Cleaning data in spreadsheets
• 4.2.3.Weekly challenge 2
• 4.2.Sparkling clean data
• 4.3.1.Using SQL to clean data
• 4.3.2.Learn basic SQL queries
• 4.3.3.Transforming data
• 4.3.4.Weekly challenge 3
• 4.3.Cleaning data with SQL
• 4.4.1.Manually cleaning data
• 4.4.2.Documenting results and the cleaning process
• 4.4.3.Weekly challenge 4
• 4.4.Verify and report on your cleaning results
• 4.5.Course challenge
• 5.1.1.Data analysis basics & Organize data for analysis
• 5.1.2.Sort data in spreadsheets & using SQL
• 5.1.3.Weekly challenge 1
• 5.1.Organizing data to begin analysis
• 5.2.1.Convert and format data
• 5.2.2.Combine multiple datasets
• 5.2.3.Weekly challenge 2
• 5.2.Formatting and adjusting data
• 5.3.1.VLOOKUP for data aggregation
• 5.3.2.Use JOINS to aggregate data in SQL
• 5.3.3.Work with subqueries
• 5.3.4.Weekly challenge 3
• 5.3.Aggregating data for analysis
• 5.4.1.Get started with data calculations
• 5.4.2.Learn more SQL calculations
• 5.4.3.The data validation process
• 5.4.4.Weekly challenge 4
• 5.4.Performing data calculations
• 5.5.Course challenge
• 5.6.bonus.Intermediate Guide to SQL
• 6.1.1.Understand data visualization
• 6.1.2.Design data visualizations
• 6.1.3.Explore visualization considerations
• 6.1.4.Weekly challenge 1
• 6.1.Visualizing data
• 6.2.1.Visualizations in Tableau
• 6.2.2.Weekly challenge 2
• 6.2.Creating data visualizations with Tableau
• 6.3.1.Use data to develop stories
• 6.3.2.Use Tableau dashboards
• 6.3.3.Weekly challenge 3
• 6.3.Crafting data stories
• 6.4.1.The art and science of an effective presentation & Identify presentation skills and practices
• 6.4.2.Caveats and limitations to data & Listen, respond, and include
• 6.4.3.Weekly challenge 4
• 6.4.Developing presentations and slideshows
• 6.5.Course challenge
• 7.1.1.Learn programming using R
• 7.1.2.Weekly challenge 1
• 7.1.Programming and data analytics
• 7.2.1.Explore coding in R
• 7.2.2.Learning about R packages
• 7.2.3.Weekly challenge 2
• 7.2.Programming using RStudio
• 7.3.1.Explore data and R
• 7.3.2.Cleaning data
• 7.3.3.Weekly challenge 3
• 7.3.Working with data in R
• 7.4.1.Create data visualization in R
• 7.4.2.Explore aesthetics in analysis
• 7.4.3.Annotate and save visualizations
• 7.4.4.Weekly challenge 4
• 7.4.More about visualizations, aesthetics, and annotations
• 7.5.1.Develop documentation and reports in RStudio
• 7.5.2.R Markdown documents & Code chunks and exports
• 7.5.3.Weekly challenge 5
• 7.5.Documentation and reports
• 7.6.Course Challenge
• 8.1.Learn about capstone basics
• 8.2.Optional: Building your portfolio
• 8.3.Optional: Using your portfolio
• Glossary
• Google Data Analytics Professional Certificate