FREE Google Data Analyst Certification
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GOOGLE Data Analytics CERTIFICATE
Google Career Certificates are taught and developed by Google employees working in these fields; they are hands-on, practical, and rigorous. Google Career Certification courses give learners the skills they need to apply for more than 2.4 million in-demand jobs with a median salary of $76,000+.
These training courses span the fields of Cybersecurity, Data Analytics, Digital Marketing & E-Commerce, IT Support, Project Management, and User Experience (UX) design.
A Google Career Certificate can be completed in under 6 months at a suggested pace of 10 hours a week or less. 75% of certificate graduates report positive career outcomes (e.g., new job, promotion, or raise) within six months of completion.
The Google Data Analytics Certificate teaches learners how to prepare, process, and analyze data to help inform business decisions.
College students can earn a recommendation of 9 college credits for completing the Google Data Analytics Certificate, that’s an
equivalent of 3 college courses at the bachelor’s degree level.
This certificate program is for anyone who wants to enter the field of Data Analytics; no prior experience or specific knowledge is required.
Google career certification success stories
FAQs
The GOOGLE Data Analytics Certificate
Prepares Learners for IN-DEMAND
Jobs, Such as:
Data Analyst
A Data Analyst is responsible for collecting, processing, and performing statistical analyses on large datasets to uncover trends, patterns, and insights that inform decision-making processes within an organization. They utilize various analytical techniques and tools to transform complex data into actionable information, supporting business strategies and objectives.
Associate Data Analyst
An Associate Data Analyst works on collecting, processing, and analyzing data to help businesses make informed decisions. They play a supportive role in interpreting data, creating reports, and using statistical tools to identify trends and insights, contributing to strategies that enhance organizational performance.
Business systems analyst
A Business Systems Analyst bridges the gap between IT and business units by assessing business needs and translating them into technical requirements for IT projects. They analyze workflows, design system solutions, and ensure the successful implementation and adoption of technology to improve efficiency, productivity, and profitability within an organization.
Junior Data Analyst
A Junior Data Analyst assists in analyzing data sets to identify trends, develop charts, and create reports that help in making data-driven decisions. Working under the guidance of senior analysts, they gather, clean, and process data, applying basic statistical methods and tools to support the analytical needs of an organization. dddddddddddddddddddddddddddddddd
Operations Analyst
An Operations Analyst evaluates and analyzes an organization’s operational processes, identifying areas for improvement to increase efficiency, reduce costs, and enhance overall performance. They use data analysis, process modeling, and simulation techniques to recommend strategic changes and solutions, supporting the optimization of day-to-day operations.
Data-Driven Decisions Made Easy: Google Data Analytics Certificate Benefits
Upon finishing the Google Data Analytics Certificate program, graduates will have acquired the following competencies:
Master Key Data Analysis Tools
Gain hands-on experience with the most sought-after data analysis platforms—spreadsheets, SQL, Tableau, and R programming—knowing precisely when and how to leverage each throughout the data lifecycle.
From Questions to Insights
Learn the art of transforming complex business questions into structured data analysis projects, encompassing data transformation, visualization, and modeling techniques for comprehensive understanding.
Actionable Insights Expertise
Develop the skill to succinctly distill complex findings into clear, actionable insights, empowering decision-makers with the information they need to drive success.
Capstone Project Completion
Complete a culminating capstone project, offering a tangible demonstration of your data analytics prowess, ready to be showcased on your resume or portfolio to impress potential employers and hiring partners.
Course Overview
01
Course 1
Foundations: Data, Data, Everywhere
02
Course 2
Ask Questions to Make Data-Driven Decisions
05
Course 5
Analyze Data to Answer Questions
06
Course 6
Share Data Through the Art of Visualization
The Complete Course Content Breakdown
297 Videos
223 Readings
136 Quizzes
86 Hands-on Activities
40 Writing Assignments
41 Discussion Prompts
Course 1 — Foundations: Data, Data, Everywhere
In this course, we cover foundational data analytics terminology and learners gain a deeper understanding of the role and responsibilities of
a data analyst. We also introduce the kinds of jobs learners might pursue after completing this program.
By the end of this course, learners will be able to:
● Learn about key analytical skills (data cleaning, data analysis, data visualization) and tools (spreadsheets, SQL, Tableau, R programming).
● Gain an understanding of the practices and processes used by
a junior or associate data analyst in their day-to-day job.
● 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.
● Explore job opportunities available upon program completion, and learn about best practices in the job search. kkkkkkkkkkkkkkkkkkkkkkkkkkkk
● Conduct an analytical thinking self-assessment.
SKILLS ACQUIRED:
❏ Spreadsheet basics
❏ Database and query basics
❏ Data visualization (DataViz) basics
TOPICS:
★ Introducing data analytics
★ Thinking analytically
★ Exploring the wonderful world of data
★ Setting up a data toolbox
★ Discovering data career possibilities
Course 1 Content Breakdown
36 Videos
28 Readings
19 Quizzes
7 Hands-on Activities
9 Writing Assignments
8 Discussion Prompts
Course 2 — Ask Questions to Make Data-Driven Decisions
In this course, we build on the topics introduced in the first course and cover how to ask effective questions to make data-driven decisions,
while connecting with stakeholders’ needs.
By the end of this course, learners will be able to:
- Learn strategies for managing the expectations of stakeholders while establishing clear communication with a data analytics team to achieve business objectives.
- 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.
- 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. hhhhhhhhhhhhh
- Learn about effective questioning techniques that can help
guide analysis.
SKILLS ACQUIRED:
❏ Spreadsheet formulas & functions
❏ Asking SMART and effective questions
❏ Dashboard basics, incl. Tableau
❏ Problem solving with data
❏ Managing team and stakeholder
expectations
TOPICS:
★ Building customer loyalty
★ Understanding e-commerce analytics
★ Merchandising
★ Searching for, applying to, and interviewing for digital marketing and e-commerce jobs
Course 2 Content Breakdown
36 Videos
25 Readings
19 Quizzes
7 Hands-on Activities
6 Writing Assignments
4 Discussion Prompts
Course 3 — Prepare Data for Exploration
In this course, we build on the topics introduced in the first two courses. We also cover how to use tools like spreadsheets and SQL to
extract and make use of the right data for key objectives and how to organize and protect data.
By the end of this course, learners will be able to:
- Find out how analysts decide which data to collect for analysis.kk
- Explore how analysts use spreadsheets and SQL with
databases and data sets.
- Learn the best practices for organizing data and
keeping it secure.
- Learn about structured and unstructured data, data types, and
data formats.
- Examine open data and the relationship between and
importance of data ethics and data privacy.
- Discover how to identify different types of bias in data to help
ensure data credibility.
- Gain an understanding of how to access databases and
extract, filter, and sort the data they contain.
SKILLS ACQUIRED:
❏ Understanding data types, fields,
and values
❏ Writing simple queries
❏ Metadata in data analytics
❏ SQL functions
TOPICS:
★ Data types and data structures
★ Understanding bias, credibility, privacy,
ethics, and access
★ Databases: where data lives
★ Organizing and protecting your data
★ [optional] Engaging in the data community
Course 7 Content Breakdown
44 Videos
31 Readings
20 Quizzes
11 Hands-on Activities
4 Writing Assignments
2 Discussion Prompts
Course 4 — Process Data from Dirty to Clean
In this course, we build on topics introduced in previous courses and we also explore how to check and clean data using spreadsheets and
SQL, as well as how to verify and report data cleaning results
By the end of this course, learners will be able to:
- Learn how to check for data integrity.
- Apply basic SQL functions for cleaning and transforming data.
- Discover data cleaning techniques using spreadsheets.
- Gain an understanding of how to verify the results of
cleaning data.
- Develop basic SQL queries for use on databases.
- Explore the elements and importance of data cleaning reports.
SKILLS ACQUIRED:
❏ Statistics, hypothesis testing,
and margin of error
❏ Tools and processes for data
cleansing
❏ Data integrity
TOPICS:
★ Before you clean, check for integrity
★ All about clean data
★ Cleaning data in SQL
★ Verify and report your cleaning results
★ [optional] Adding data to your resume
Course 4 Content Breakdown
43 Videos
27 Readings
16 Quizzes
10 Hands-on Activities
4 Writing Assignments
3 Discussion Prompts
Course 5 — Analyze Data to Answer Questions
In this course, we explore the “analyze” phase of the data analysis process. We cover how to organize and format your data using
spreadsheets and SQL to help you look at and think about your data in different ways.
We also explore how to perform complex calculations on data to complete business objectives. Additionally, we teach how to use formulas, functions, and SQL queries to conduct analysis.
By the end of this course, learners will be able to:
- Learn how to organize data for analysis.
- Use formulas and functions in spreadsheets for data calculations.
- Discover the processes for formatting and adjusting data.
- Learn how to complete calculations using SQL queries.
- Gain an understanding of how to aggregate data in spreadsheets and by using SQL.
SKILLS ACQUIRED:
❏ Reaching customers online
❏ Managing client relationships
❏ Building loyalty with e-commerce customers
❏ Putting together a portfolio
❏ Presenting work and ideas
❏ Handling rejection
❏ Preparing for job applications and interviews
❏ Developing a resume
TOPICS:
★ Building customer loyalty
★ Understanding e-commerce analytics
★ Merchandising
★ Searching for, applying to, and interviewing for digital marketing and e-commerce jobs
Course 5 Content Breakdown
41 Videos
28 Readings
19 Quizzes
14 Hands-on Activities
3 Writing Assignment
3 Discussion Prompts
Course 6 — Share Data Through the Art of Visualization
In this course, we explore how to visualize and present data findings during the data analysis process. We demonstrate how data
visualizations, such as visual dashboards, can help bring data to life.
We also explore Tableau, a data visualization platform that helps create effective visualizations for presentations.
By the end of this course, learners will be able to:
- Examine the importance of data visualization.
- Gain an understanding of how to use Tableau to create dashboards and dashboard filters.
- Learn how to form a compelling narrative through data stories.
- Explore the principles and practices involved with
effective presentations.
- Understand how to apply best practices to a Q&A with your audience.
- Discover how to use Tableau to create effective visualizations.
- Learn how to consider potential limitations associated with the
data in your presentations.
SKILLS ACQUIRED:
❏ Design thinking
❏ Tableau software
❏ Data-driven storytelling
❏ Dashboards and dashboard filters
TOPICS:
★ Visualizing data
★ Creating data visualizations with Tableau
★ Crafting data stories
★ Developing presentations and slideshows
Course 6 Content Breakdown
42 Videos
26 Readings
10 Quizzes
10 Hands-on Activities
8 Writing Assignment
7 Discussion Prompts
Course 7 — Data Analysis with R Programming
In this course, we explore the programming language known as R. We cover how to use RStudio, the environment that allows data analysts to work with R. This course also covers the software applications and tools that are unique to R, such as R packages.
We also discover how to clean, organize, analyze, visualize, and report data in new and more powerful ways using R.
By the end of this course, learners will be able to:
- Examine the benefits of using the R programming language.
- Explore the contents and components of R packages including the Tidyverse package.
- Learn about R Markdown for documenting R programming.
- Discover how to use RStudio to apply R to data analysis.
- Gain an understanding of dataframes and their use in R.
- Explore the fundamental concepts associated with programming in R.
- Discover the options for generating visualizations in R.
SKILLS ACQUIRED:
❏ R programming functions, variables,
data types, pipes, and vectors
❏ Coding, writing functions, accessing
and cleaning data, and generating
visualizations in R
TOPICS:
★ Programming and data analytics
★ Programming using Rstudio
★ Working with data in R programming
★ More about visualizations, aesthetics,
and annotations
★ Documentation and reports
Course 7 Content Breakdown
39 Videos
35 Readings
21 Quizzes
23 Hands-on Activities
2 Discussion Prompts
8 Discussion Prompts
Course 8 — Capstone: Complete a Case Study
In this course, learners have the opportunity to complete an optional case study, which help them prepare for the data analytics job hunt.
Case studies are commonly used by employers to assess analytical skills.
For their case study, they’ll choose an analytics-based scenario. They’ll then ask questions, prepare, process, analyze, visualize and act on the data from the scenario. We also cover other useful job hunt skills through videos with common interview questions and responses, helpful materials to build a portfolio online, and more.
By the end of this course, learners will be able to:
- Learn the benefits and uses of case studies and portfolios in
the job search.
- Examine and consider different case study scenarios.
- Explore real world job interview scenarios and common
interview questions.
- Have the chance to complete your own case study for
your portfolio.
- Discover how case studies can be a part of the job
interview process.
SKILLS ACQUIRED:
❏ Building a job portfolio
❏ Practical, real-world problem solving
❏ Clear presentation of data findings
❏ Showcasing data analytics skills,
knowledge, and technical expertise
TOPICS:
★ Learn about capstone basics
★ [optional] Building your portfolio
★ [optional] Using your portfolio
★ Putting your certificate to work
Course 8 Content Breakdown
16 Videos
23 Readings
5 Quizzes
4 Hands-on Activities
4 Writing Assignment
6 Discussion Prompts
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