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Data Responsibility

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Data Responsibility

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Gain insight into a topic and learn the fundamentals.
4.8

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Beginner level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.8

10 reviews

Beginner level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Discuss the difference between biased and unbiased data.

  • Discuss characteristics of credible sources of data including reference to untidy data

  •  Explain the relationship between data ethics and data privacy

  • Demonstrate an awareness of the accessibility issues associated with open data

Details to know

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Assessments

6 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Google Data-Driven Decision Making Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

Before you work with data, you must confirm that it is unbiased and credible. After all, if you start your analysis with unreliable data, you won’t be able to trust your results. In this course, you will learn to identify bias in data and to ensure your data is credible. You’ll also explore open data and the importance of data ethics and data privacy.

By the end of this course, you will be able to: - Explain what is involved in reviewing data to identify bias - Discuss the difference between biased and unbiased data - Identify different types of bias including confirmation, interpretation, and observer bias - Discuss characteristics of credible sources of data including reference to untidy data - Explain the concept of open data with reference to the ongoing debate in data analytics - Define data ethics and data privacy - Explain the relationship between data ethics and data privacy - Demonstrate an understanding of the benefits of anonymizing data - Demonstrate an awareness of the accessibility issues associated with open data

As a data analyst, it is important to understand why reaching conclusions on biased data can have real-world effects. In this part of the course, you'll learn what bias is, how it affects data, the types of bias, and how to spot it.

What's included

4 videos1 reading1 assignment

4 videos•Total 10 minutes
  • Introduction to bias, credibility, privacy, and ethics•1 minute
  • Bias: From questions to conclusions•3 minutes
  • Biased and unbiased data•2 minutes
  • Understand bias in data•4 minutes
1 reading•Total 1 minute
  • Welcome to “Data Responsibility”•1 minute
1 assignment•Total 8 minutes
  • Test your knowledge on unbiased and objective data •8 minutes

In this part of the course, you will learn to identify bias in data and to ensure your data is credible.

What's included

2 videos1 assignment

2 videos•Total 6 minutes
  • Identify good data sources•3 minutes
  • What is "bad" data?•3 minutes
1 assignment•Total 8 minutes
  • Test your knowledge on data credibility•8 minutes

You’ll explore the importance of data ethics and data privacy.

What's included

4 videos1 reading1 assignment

4 videos•Total 13 minutes
  • Essential data ethics•5 minutes
  • Optional refresher: Alex and the importance of data ethics•3 minutes
  • Prioritize data privacy•2 minutes
  • Andrew: The ethical use of data•3 minutes
1 reading•Total 4 minutes
  • Data anonymization•4 minutes
1 assignment•Total 8 minutes
  • Test your knowledge on data ethics and privacy •8 minutes

In this part of the course, you'll explore and understand open data.

What's included

2 videos2 readings3 assignments

2 videos•Total 7 minutes
  • Features of open data•4 minutes
  • Andrew: Steps for ethical data use•3 minutes
2 readings•Total 12 minutes
  • The open data debate•4 minutes
  • Resources for open data•8 minutes
3 assignments•Total 108 minutes
  • Hands-On Activity: Kaggle datasets•60 minutes
  • Test your knowledge on open data•8 minutes
  • Course 5 challenge: Data responsibility•40 minutes

Earn a career certificate

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Instructor

Google
386 Courses•16,905,595 learners

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Frequently asked questions

Data is a group of facts that can take many different forms, such as numbers, pictures, words, videos, observations, and more. We use and create data everyday, like when we stream a show or song or post on social media.

Data analytics is the collection, transformation, and organization of these facts to draw conclusions, make predictions, and drive informed decision-making.

No experience with spreadsheets or data analytics is required. All you need is high-school level math and a curiosity about how things work.

You don't need to be a math all-star to succeed in this certificate. You need to be curious and open to learning with numbers (the language of data analysts). Being a strong data analyst is more than just math—it's about asking the right questions, finding the best sources to answer your questions effectively, and illustrating your findings clearly in visualizations.

We highly recommend taking the courses in the order presented, as the content builds on information from earlier courses. This is the fifth course in a series of nine courses that make up the Google Data-Driven Decision Making Specialization.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,