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quanganh2001 / Google-Data-Analytics-Professional-Certificate-Coursera Public

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quanganh2001 edited this page Apr 6, 2023 · 1 revision

Welcome to the Google-Data-Analytics-Professional-Certificate-Coursera wiki!

Toggle table of contents Pages 215

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Home
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1.2.0.Thinking analytically
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1.2.1.Embracing Data Analyst Skills
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1.2.2.Thinking about Analytical Thinking
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1.2.3.Thinking about outcomes
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1.2.4.Weekly challenge 2
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1.3.0.The wonderful world of data
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1.3.1.Follow the data life cycle
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1.3.2.Outlining the data analysis process
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1.3.3.The data analysis toolbox
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1.3.4.Weekly challenge 3
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1.4.0.Set up your toolbox
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1.4.1.Mastering spreadsheet basics
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1.4.2.Structured Query Language (SQL)
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1.4.3.Data visualization
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1.4.4.Weekly challenge 4
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1.4.5.Video quiz
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1.5.0.Endless career possibilities
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1.5.1.Data analyst job opportunities
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1.5.2.The importance of fair business decisions
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1.5.3.Optional: Exploring your next job
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1.5.4.Weekly challenge 5
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1.5.5.Course challenge
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1.5.6.Video quiz
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2.1.0.Effective questions
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2.1.1.Problem solving and effective questionning
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2.1.2.Take action with data
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2.1.3.Solve problems with data
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2.1.4.Craft effective questions
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2.1.5.Weekly challenge 1
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2.1.6.Video quiz
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2.2.0.Data driven decisions
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2.2.1.Understand the power of data
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2.2.2.Follow thje evidence
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2.2.3.Connecting the data dots
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2.2.4.Weekly challenge 2
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2.2.5.Video quiz
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2.3.0.More spreadsheet basics
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2.3.1.Working with spreadsheets
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2.3.2.Formulas in spreadsheets
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2.3.3.Functions in spreadsheets
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2.3.4.Save time with structured thinking
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2.3.5.Weekly challenge 3
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2.3.6.Video quiz
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2.4.0.Always remember the stakeholder
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2.4.1.Balance team and stakeholder needs
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2.4.2.Communication is key
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2.4.3.Amazing teamwork
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2.4.4.Weekly challenge 4
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2.4.5.Course challenge
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2.4.6.Video quiz
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3.1.0.Data types and structures
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3.1.1.Data exploration
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3.1.2.Collecting data
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3.1.3.Differentiate between data formats and structures
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3.1.4.Explore data types, fields, and values
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3.1.5.Weekly challenge
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3.1.6.Video quiz
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3.2.0.Bias, credibility, privacy, ethics, and access
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3.2.1.Unbiased and objective data
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3.2.2.Explore data credibility
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3.2.3.Data ethics and privacy
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3.2.4.Understanding open data
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3.2.5.Weekly challenge 2
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3.2.6.Video quiz
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3.3.0.Databases: Where data lives
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3.3.1.Working with databases
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3.3.2.Managing data with metadata
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3.3.3.Accessing different data sources
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3.3.4.Sorting and filtering
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3.3.5.Working with large datasets in SQL
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3.3.6.Weekly challenge 3
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3.3.7.Video quiz
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3.4.0.Organizing and protecting your data
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3.4.1.Effectively organize data
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3.4.2.Securing data
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3.4.3.Weekly challenge 4
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3.5.0.Optional: Engaging in the data community
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3.5.1.Create or enhance your online presence
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3.5.2.Build a data analytics network
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3.5.3.Course challenge
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3.5.4.Video quiz
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4.1.0.The importance of integrity
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4.1.1.Focus on integrity
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4.1.2.Data integrity and analytics objectives
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4.1.3.Overcoming the challenges of insufficient data
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4.1.4.Testing your data
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4.1.5.Consider the margin of error
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4.1.6.Weekly challenge 1
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4.1.7.Video quiz
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4.2.0.Sparkling clean data
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4.2.1.Data cleaning is a must
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4.2.2.Begin cleaning data
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4.2.3.Cleaning data in spreadsheets
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4.2.4.Weekly challenge 2
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4.2.5.Video quiz
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4.3.0.Cleaning data with SQL
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4.3.1.Using SQL to clean data
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4.3.2.Learn basic SQL queries
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4.3.4.Weekly challenge 3
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4.3.5.Video quiz
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4.4.0.Verify and report on your cleaning reports
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4.4.1.Manually cleaning data
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4.4.2.Documenting results and the cleaning process
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4.4.3.Weekly challenge 4
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4.4.4.Video quiz
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4.5.0.Optional: Adding data to your resume
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4.5.1.The data analyst hiring process
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4.5.2.Understand the elements of a data analyst resume
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4.5.3.Highlighting experiences on resumes
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4.5.4.Exploring areas of interest
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4.5.6.Course challenge
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5.1.0.Organizing data to begin analysis
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5.1.1.Let's get organized
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5.1.2.Data analytics basics
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5.1.3.Organize data for analysis
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5.1.4.Sort data in spreadsheets
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5.1.5.Sort data using SQL
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5.1.6.Weekly challenge 1
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5.1.7.Video quiz
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5.2.0.Formatting and adjusting data
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5.2.1.Convert and format data
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5.2.2.Combine multiple datasets
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5.2.3.Get support during analysis
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5.2.4.Weekly challenge 2
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5.2.5.Video quiz
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5.3.0.Aggregating data for analysis
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5.3.1.VLOOKUP for data aggregation
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5.3.2.Use JOINS to aggregate data in SQL
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5.3.3.Work with subqueries
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5.3.4.Weekly challenge 3
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5.3.5.Video quiz
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5.4.0.Performing data calculations
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5.4.1.Get started with data calculations
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5.4.2.Pivot...Pivot...Pivot
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5.4.3.Learn more SQL calculations
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5.4.4.The data validation process
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5.4.5.Using SQL with temporary tables
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5.4.6.Weekly challenge 4
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5.4.7.Course challenge
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5.4.8.Video quiz
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6.1.0.Visualizing data
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6.1.1.Communicating your data insights
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6.1.2.Understand data visualization
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6.1.3.Design data visualizations
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6.1.4.Explore visualization considerations
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6.1.5.Weekly challenge 1
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6.1.6.Video quiz
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6.2.0.Creating data visualizations with Tableau
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6.2.1.Get started with Tableau
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6.2.2.Create visualizations in Tableau
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6.2.3.Optional: Work with multiple data sources
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6.2.4.Weekly challenge 2
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6.2.5.Video quiz
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6.3.0.Crafting data stores
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6.3.1.Use data to develop stories
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6.3.2.Use Tableau dashboards
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6.3.3.Sharing data stories
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6.3.4.Weekly challenge 3
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6.3.5.Video quiz
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6.4.0.Developing presentations and slideshows
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6.4.1.The art and science of an effective presentation
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6.4.2.Identify presentation skills and practices
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6.4.3.Caveats and limitations to data
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6.4.4.Listen, respond, and include
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6.4.5.Weekly challenge 4
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6.4.6.Course wake‐up
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6.4.7.Video quiz
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6.5.0.Documentation and reports
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6.5.6.Video quiz
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7.1.0.Programming and data analytics
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7.1.1.The exciting world of programming
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7.1.2.Programming as a data analyst
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7.1.3.Learn programming using RStudio
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7.1.4.Weeky challenge 1
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7.1.5.Video quiz
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7.2.0.Programming using RStudio
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7.2.1.Understand basic programming concepts
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7.2.2.Explore coding in R
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7.2.3.Learning about R packages
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7.2.4.Explore the tidyverse
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7.2.5.Weekly challenge 2
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7.2.6.Video quiz
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7.3.0.Working with data in R
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7.3.1.Explore data and R
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7.3.2.Cleaning data
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7.3.3.Take a closer look at the data
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7.3.4.Weekly challenge 3
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7.3.5.Video quiz
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7.4.0.More about visualizations, aesthetics, and annotations
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7.4.1.Create data visualization in R
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7.4.2.Explore aesthetics in analysis
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7.4.3.Annotate and save visualizations
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7.4.4.Weekly challenge 4
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7.4.5.Video quiz
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7.5.0.Documentation and reports
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7.5.1.Develop documentation and reports in RStudio
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7.5.2.Create R Markdown documents
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7.5.3.Understand code chunks and exports
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7.5.4.Weekly challenge 5
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7.5.5.Course wrap‐up
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7.5.6.Video quiz
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Week 1: Get started Part 01. Program description and course syllabus
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Week 1: Get started Part 02. Learning Log: Think about data in daily life
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Week 1: Get started Part 03. Helpful resources to get started
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Week 1: Get started Part 04. Meet and greet
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Week 1: Get started Part 05. Deciding if you should take the speed track
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Week 1: Get started Part 06. Diagnostic Quiz
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Week 1: Glossary: Terms and definitions
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Week 1: Transforming data into insights Part 01. Case study: New data perspectives
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Week 1: Transforming data into insights Part 02. Learning Log: Consider how data analysts approach tasks
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Week 1: Understanding the data ecosystem Part 01. Data and gut instinct
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Week 1: Understanding the data ecosystem Part 02. Origins of the data analysis process
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Week 1: Understanding the data ecosystem Part 03. Test your knowledge on the data ecosystem
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Weekly challenge 1

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