Foundations: Data, Data, Everywhere
4.7 /5- Offered byCoursera
Foundations: Data, Data, Everywhere at Coursera Overview
Duration | 21 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Foundations: Data, Data, Everywhere at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 1 of 8 in the Google Data Analytics
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level No prior experience with spreadsheets or data analytics required. All you need is high school level math and curiosity about how things work.
- Approx. 21 hours to complete
- English Subtitles: English
Foundations: Data, Data, Everywhere at Coursera Course details
- This is the first course in the Google Data Analytics Certificate. These courses will equip you with the skills you need to apply to introductory-level data analyst jobs. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions. In this course, you?ll be introduced to the world of data analytics through hands-on curriculum developed by Google. The material shared covers plenty of key data analytics topics, and it?s designed to give you an overview of what?s to come in the Google Data Analytics Certificate. Current Google data analysts will instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.
- Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.
- By the end of this course, you will:
- - 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.
Foundations: Data, Data, Everywhere at Coursera Curriculum
Introducing data analytics
Welcome to the Google Data Analytics Certificate
Introduction to the course
Data analytics in everyday life
Cassie: Dimensions of data analytics
What is the data ecosystem?
How data informs better decisions
What to expect moving forward
Program description and course syllabus
Learning Log: Think about data in daily life
Helpful resources to get started
Deciding if you should take the speed track
Optional: Your diagnostic quiz score and what it means
Case Study: New data perspectives
Learning Log: Consider how data analysts approach tasks
Data and gut instinct
Origins of the data analysis process
Program surveys
Discussion forums
Get to know your classmates
Glossary: Terms and definitions
Optional: Familiar with data analytics? Take our diagnostic quiz
Test your knowledge on the data ecosystem
Test your knowledge on program expectations
*Weekly challenge 1*
Thinking analytically
Discovering data skill sets
Key data analyst skills
All about thinking analytically
Exploring core analytical skills
Using data to drive successful outcomes
Real-world data magic
Learning Log: Explore data from your daily life
Learning Log: Reflect on your skills and expectations
Glossary: Terms and definitions
Get a read on your analytical skills
Self-Reflection: What you bring to the table
Test your knowledge on analytical thinking
Test your knowledge on outcomes
*Weekly challenge 2*
Exploring the wonderful world of data
Learning about data phases and tools
Phases of the data life cycle
Six phases of data analysis
Molly: Example of the data process
Exploring data analyst tools
The data analysis process and this program
Learning Log: Organize your data in a table
Key data analyst tools
Choosing the right tool for the job
Glossary: Terms and definitions
Self-Reflection: Collecting data
Test your knowledge on the data life cycle
Test your knowledge on the data analysis process
Self-Reflection: Reviewing past concepts
Test your knowledge on the data analysis toolbox
*Weekly challenge 3*
Setting up a data toolbox
The ins and outs of core data tools
Columns and rows and cells, oh my!
SQL in action
Angie: Everyday struggles when learning new skills
Becoming a data viz whiz
Lilah: The power of a visualization
Evan: How to access Qwiklabs
Evan: Hands-on with Qwiklabs
Evan: How to get chat support in a Qwiklab
More spreadsheet resources
More about SQL in action
SQL Guide: Getting started
Planning a data visualization
Get ready for Qwiklabs
Step-by-step instructions for accessing Qwiklabs
Glossary: Terms and definitions
Hands-On Activity: Generating a chart from a spreadsheet
Test your knowledge on spreadsheet basics
Test your knowledge on SQL
Test your knowledge on visualizing data
*Weekly challenge 4*
Discovering data career possibilities
Let's get down to business
The job of a data analyst
Joey: Path to becoming a data analyst
Tony: Supporting careers in data analytics
The power of data in business
Rachel: Data detectives
Understanding data and fairness
Alex: Fair and ethical data decisions
Data analysts in different industries
Samah: Interview best practices
Weekly wrap-up
Congrats! Course wrap-up
Learning Log: Reflect on the data analysis process
Data analyst roles and job descriptions
Beyond the Numbers: A Data Analyst Journey
Glossary: Terms and definitions
Coming up next...
Self-Reflection: Business use of data
Self-Reflection: Business cases
Test your knowledge on making fair business decisions
*Weekly challenge 5*
*Course challenge*
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