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Google Data Analytics Professional Certificate

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Google INSTRUCTORS

Instructors: Google Employees

Course Description

Prepare for a new career in the high-growth field of data analytics, no experience or degree required. Get professional training designed by Google and have the opportunity to connect with top employers. There are 380,000 U.S. job openings in data analytics with a $74,000 median entry-level salary.¹

Data analytics is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision making.

Over 8 courses, gain in-demand skills that prepare you for an entry-level job. You’ll learn from Google employees whose foundations in data analytics served as launchpads for their own careers. At under 10 hours per week, you can complete the certificate in less than 6 months.

Course 1 - Foundations: Data, Data, Everywhere

  • Gain an understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job.
  • Learn about key analytical skills (data cleaning, data analysis, data visualization) and tools (spreadsheets, SQL, R programming, Tableau) that you can add to your professional toolbox.
  • Discover a wide variety of terms and concepts relevant to the role of a junior data analyst, such as the data life cycle and the data analysis process.
  • Evaluate the role of analytics in the data ecosystem.
  • Conduct an analytical thinking self-assessment.
  • Explore job opportunities available to you upon program completion, and learn about best practices in the job search.

Course 2 - Ask Questions to Make Data-Driven Decisions

  • Learn about effective questioning techniques that can help guide analysis.
  • Gain an understanding of data-driven decision-making and how data analysts present findings.
  • Explore a variety of real-world business scenarios to support an understanding of questioning and decision-making.
  • Discover how and why spreadsheets are an important tool for data analysts.
  • Examine the key ideas associated with structured thinking and how they can help analysts better understand problems and develop solutions.
  • Learn strategies for managing the expectations of stakeholders while establishing clear communication with a data analytics team to achieve business objectives.

Course 3 - Prepare Data for Exploration

  • Find out how analysts decide which data to collect for analysis.
  • Learn about structured and unstructured data, data types, and data formats.
  • Discover how to identify different types of bias in data to help ensure data credibility.
  • Explore how analysts use spreadsheets and SQL with databases and data sets.
  • Examine open data and the relationship between and importance of data ethics and data privacy.
  • Gain an understanding of how to access databases and extract, filter, and sort the data they contain.
  • Learn the best practices for organizing data and keeping it secure.

Course 4 - Process Data from Dirty to Clean

  • Learn how to check for data integrity.
  • Discover data cleaning techniques using spreadsheets.
  • Develop basic SQL queries for use on databases.
  • Apply basic SQL functions for cleaning and transforming data.
  • Gain an understanding of how to verify the results of cleaning data.
  • Explore the elements and importance of data cleaning reports.

Course 5 - Analyze Data to Answer Questions

  • Learn how to organize data for analysis.
  • Discover the processes for formatting and adjusting data.
  • Gain an understanding of how to aggregate data in spreadsheets and by using SQL.
  • Use formulas and functions in spreadsheets for data calculations.
  • Learn how to complete calculations using SQL queries.

Course 6 - Share Data Through the Art of Visualization

  • Examine the importance of data visualization.
  • Learn how to form a compelling narrative through data stories.
  • Gain an understanding of how to use Tableau to create dashboards and dashboard filters.
  • Discover how to use Tableau to create effective visualizations.
  • Explore the principles and practices involved with effective presentations.
  • Learn how to consider potential limitations associated with the data in your presentations.
  • Understand how to apply best practices to a Q&A with your audience.

Course 7 - Data Analysis with R Programming

  • Examine the benefits of using the R programming language.
  • Discover how to use RStudio to apply R to your analysis.
  • Explore the fundamental concepts associated with programming in R.
  • Explore the contents and components of R packages including the Tidyverse package.
  • Gain an understanding of dataframes and their use in R.
  • Discover the options for generating visualizations in R.
  • Learn about R Markdown for documenting R programming.

Course 8 - Google Data Analytics Capstone: Complete a Case Study

  • Learn the benefits and uses of case studies and portfolios in the job search.
  • Explore real world job interview scenarios and common interview questions.
  • Discover how case studies can be a part of the job interview process.
  • Examine and consider different case study scenarios.
  • Have the chance to complete your own case study for your portfolio.