foundations of data science coursera week 2 quiz answers

Test your knowledge: Data-driven careers

1. What type of data professionals are business intelligence professionals and technical project managers?

  • Technical
  • Governance
  • Information technology
  • Strategic

2. Fill in the blank: Expert _____ explore vast and complex datasets in order to identify worthwhile business initiatives.

  • data analysts
  • project managers
  • data governance professionals
  • stakeholders

Test your knowledge: Doing good with data analytics

3. What is the term for organizations that are specifically created to foster a collective, public, or social advantage, rather than maximizing revenue?

  • Corporations
  • Governments
  • Cooperatives
  • Nonprofits

4. A data professional collects feedback from many different individuals, then gathers it together to inform a data project. What does this scenario describe?

  • Cross-sectioning
  • Aggregation
  • Visualizing
  • Spotlighting

Test your knowledge: Trajectory of the field

5. Fill in the blank: Artificial intelligence is the development of _____ able to perform tasks that normally require human intelligence.

  • computer systems
  • business intelligence tools
  • statistics
  • models

6. In what way is building diverse teams an effective method for countering human bias in data work? Select all that apply.

  • It eliminates outliers in the data.
  • It incorporates a wide range of perspectives.
  • It promotes wider representation.
  • It yields more accurate project results.

7. What are some typical responsibilities of technical data professionals? Select all that apply.

  • Transform raw data into useful information
  • Explore datasets
  • Create business intelligence dashboards
  • Build models and make predictions

8. What do data professionals do during a hackathon?

  • Collaborate to solve a problem using technology
  • Gain unauthorized access to computer systems
  • Vote on the best new data analysis software
  • Install the latest information technology hardware

9. Fill in the blank: A national identification number is an example of _____, which may permit someone’s identity to be inferred, either by direct or indirect means.

  • digital identification
  • mapped data
  • identity analytics
  • personally identifiable information

10. A data team collects information from enough people to ensure the information represents the population as a whole. What does this scenario describe?

  • Aliasing
  • Aggregating
  • A/B testing
  • Affiliating

11. Fill in the blank: A good sample is a segment of a population that is _____ the entire population.

  • more diverse than
  • representative of
  • atypical of
  • less diverse than

12. Fill in the blank: Artificial intelligence is the development of computer systems that are able to perform tasks that normally require _____ intelligence.

  • machine
  • business
  • human
  • market

13. At a business, who is responsible for ensuring socially beneficial and inclusive practices, applying scientific and ethical principles, and staying aware of possible bias?

  • Only business intelligence professionals
  • Only information technology professionals
  • All data professionals
  • Only project managers

14. A data professional is at an event collaborating with programmers and other data professionals to create a solution to an existing problem using technology. What type of an event are they attending?

  • Expo
  • Networking luncheon
  • Hackathon
  • Industry conference

15. What are the key benefits of aggregate information? Select all that apply.

  • Eliminate outliers from datasets
  • Protect individuals
  • Give people more control over their data
  • Increase the likelihood that the data represents the population as a whole

16. Fill in the blank: Artificial intelligence is the development of _____ that are able to perform tasks that normally require human intelligence.

  • computer systems
  • dashboards
  • hardware tools
  • databases

17. A data manager brainstorms ways to ensure that the experiences and worldviews of their team members do not affect data team projects. They establish processes for impartially analyzing and communicating sensitive information. What does this scenario describe?

  • Generating data from communication
  • Establishing data security procedures
  • Avoiding subtle biases in data work
  • Protecting customer or user privacy

18. Which of the following are examples of strategic data professional roles? Select all that apply.

  • Statisticians
  • Technical project managers
  • Business intelligence professionals
  • Machine learning engineers

19. What are some examples of personally identifiable information? Select all that apply.

  • Biometric records
  • Company names
  • National identification numbers
  • Usernames

20. A good sample is a segment of a population that is representative of what?

  • Half the population
  • A portion of the population
  • The outliers within the population
  • The entire population

21. A team of data professionals discusses the potential of their personal backgrounds and beliefs affecting their data findings. They establish processes to ensure that they interpret and communicate sensitive information impartially. What does this scenario describe?

  • Avoiding subtle biases in data work
  • Protecting customer or user privacy
  • Preventing data security breaches
  • Generating data from communication

22. Which of the following are examples of technical data professional roles? Select all that apply.

  • Statisticians
  • Expert data analysts
  • Machine learning engineers
  • Business intelligence professionals

23. What is the term for data that can be used to determine an individual’s identity, either by direct or indirect means?

  • Personal data map
  • Personally identifiable information
  • Digital identifier
  • Identity analytics

24. Fill in the blank: A good _____ is a segment of a population that is representative of the entire population.

  • observation
  • cluster
  • sample
  • variety

25. A data professional considers ways that their personal beliefs may inadvertently affect their work. They establish processes to ensure they collect and communicate sensitive information impartially. What does this scenario describe?

  • Establishing data security procedures
  • Avoiding subtle biases in data work
  • Generating data from communication
  • Protecting customer or user privacy

Leave a Reply