Data Literacy – What is it and why does it matter? from Coursera

You might already know that data is not neutral. Our values and assumptions are influenced by the data surrounding us - the data we create, the data we collect, and the data we share with each other. Economic needs, social structures, or algorithmic biases can have profound consequences for the way we collect and use data. Most often, the result is an increase of inequity in the world. Data also changes the way we interact. It shapes our thoughts, our feelings, our preferences and actions. It determines what we have access to, and what not. It enables global dissemination of best practices and life improving technologies, as well as the spread of mistrust and radicalization. This is why data literacy matters.

A key principle of data literacy is to have a heightened awareness of the risks and opportunities of data-driven technologies and to stay up-to-date with their consequences. In this course, we view data literacy from three perspectives: Data in personal life, data in society, and data in knowledge production. The aim is threefold: 1. To expand your skills and abilities to identify, understand, and interpret the many roles of digital technologies in daily life. 2. To enable you to discern when data-driven technologies add value to people’s lives, and when they exploit human vulnerabilities or deplete the commons. 3. To cultivate a deeper understanding of how data-driven technologies are shaping knowledge production and how they may be realigned with real human needs and values.

The course is funded by Erasmus+ and developed by the 4EU+ University Alliance including Charles University (Univerzita Karlova), Sorbonne Unviersity (Sorbonne Université), University of Copenhagen (Københavns Universitet), University of Milan (Università degli studi di Milano), and University of Warsaw (Uniwersytet Warszawski).

What's inside

Syllabus

Your Life as Data

If you use Google and have a look at your Google Dashboard you will probably be amazed by how much data this company has collected about your online activities. Now think about all the other internet services, social media sites, and databases that may have a file on you, your health, your actions and inclinations. In this module, we will explore user tracking and information harvesting, define personal data and discuss the limits in managing your personal data disclosure. Consequently, we will present the legal framework for data protection and processing.

Networked Data, Truth and Democracy

In this module we expand on Module 1 by looking at how networked data and algorithms affect the way we see the world. From global dissemination of best practices and life improving technologies to the spread of hate and radicalization, we trace the mechanisms by which data-driven technologies can add value to people’s lives, and how they can exploit human vulnerabilities.

Data-driven Knowledge Production

Big data and novel computational methods have revolutionized the way we create knowledge. We will show by example how this knowledge is used and what it implies for the future of humanity. We look at AI-research, computational social science, machine learning and education, and through these examples, we will try to cultivate a deeper understanding of how data-driven technologies are shaping the social fabric, how they augment human capabilities, and may improve our stewardship of spaceship earth.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Designed for learners getting started with data literacy

Covers essential concepts in personal life, society, and knowledge production

Helps learners become more aware of digital technologies' risks and opportunies

Provides a foundation for further studies in data literacy

Taught by experts from leading universities

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Literacy – What is it and why does it matter? with these activities:

Organize and annotate your notes, assignments, and quizzes

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Improve your ability to locate and utilize course materials

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Review your notes, assignments, and quizzes
Organize your materials by topic or concept
Annotate your materials with additional notes or summaries

Review regression methods

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Develop a strong foundation in regression methods to better understand the course materials

Browse courses on Regression Analysis

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Review the basics of regression analysis, including simple linear regression and multiple regression
Practice fitting regression models using statistical software
Interpret the results of regression analysis and draw conclusions

Read "Data Science for Business" by Foster Provost and Tom Fawcett

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Gain a deeper understanding of the business applications of data science

View Data Science for Business: What You Need to... on Amazon

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Read the book and take notes on key concepts and case studies
Identify how the concepts covered in the book apply to your own work or career goals

Five other activities

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Compile a data dictionary for a real-world dataset

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Gain hands-on experience in understanding and documenting real-world data

Browse courses on Data Management

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Identify and gather relevant metadata about the dataset
Define the variables in the dataset, including their names, types, and possible values
Create a comprehensive data dictionary that documents the structure and content of the dataset

Attend a data science hackathon

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Experience hands-on problem-solving and collaboration in a competitive environment

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Register for a data science hackathon and form a team
Work together to develop a data-driven solution to the hackathon challenge
Present your solution to a panel of judges

Practice data cleaning exercises

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Enhance data manipulation skills through repetitive exercises

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Identify and correct common data errors, such as missing values
Handle outliers and extreme values in the dataset
Transform and prepare data for analysis

Develop a data visualization dashboard

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Apply data visualization techniques to present insights from real-world data

Browse courses on Data Visualization

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Choose an appropriate dataset and identify the key insights to be conveyed
Select and use appropriate visualization techniques to effectively communicate the insights
Create an interactive dashboard that allows users to explore the data and findings

Contribute to open-source data science projects

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Gain practical experience and contribute to the data science community

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Identify open-source data science projects aligned with your interests
Review the project documentation and contribute to discussions
Submit code contributions, bug fixes, or new features

Career center

Learners who complete Data Literacy – What is it and why does it matter? will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make better decisions. This course can help build a foundation for a career as a Data Analyst by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their knowledge of data to build models and algorithms that can be used to make predictions and recommendations. This course can help build a foundation for a career as a Data Scientist by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

See salaries and explore the career path for Data Scientist

Business Analyst

Business Analysts use their knowledge of data to help businesses understand their customers, identify opportunities, and make better decisions. This course can help build a foundation for a career as a Business Analyst by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers use their knowledge of data to help businesses understand their customers, identify opportunities, and make better decisions. This course can help build a foundation for a career as a Market Researcher by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Product Manager

Product Managers use their knowledge of data to help businesses develop and launch new products. This course can help build a foundation for a career as a Product Manager by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

See salaries and explore the career path for Product Manager

Operations Research Analyst

Operations Research Analysts use their knowledge of data to help businesses improve their operations. This course can help build a foundation for a career as an Operations Research Analyst by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Financial Analyst

Financial Analysts use their knowledge of data to help businesses make investment decisions. This course can help build a foundation for a career as a Financial Analyst by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Consultant

Consultants use their knowledge of data to help businesses solve problems. This course can help build a foundation for a career as a Consultant by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Data Journalist

Data Journalists use their knowledge of data to tell stories and inform the public. This course may be useful for a career as a Data Journalist by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Information Architect

Information Architects use their knowledge of data to design and organize websites and other digital products. This course may be useful for a career as an Information Architect by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Web Developer

Web Developers use their knowledge of data to develop websites and other digital products. This course may be useful for a career as a Web Developer by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Software Engineer

Software Engineers use their knowledge of data to develop software applications. This course may be useful for a career as a Software Engineer by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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User Experience Designer

User Experience Designers use their knowledge of data to design and test websites and other digital products. This course may be useful for a career as a User Experience Designer by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Graphic designer

Graphic Designers use their knowledge of data to create visual representations of information. This course may be useful for a career as a Graphic Designer by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

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Writer

Writers use their knowledge of data to communicate information to others. This course may be useful for a career as a Writer by providing an understanding of the principles of data literacy, the different types of data, and how to use data to solve problems.

See salaries and explore the career path for Writer