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Beth Prince-Bradbury

In Data Literacy Foundations, you will learn how critical thinking is an essential data literacy skill in today’s data-driven world. You’ll begin by considering how you use data every day, discussing the value of data and examining the transformation of data from analogue to digital forms.

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In Data Literacy Foundations, you will learn how critical thinking is an essential data literacy skill in today’s data-driven world. You’ll begin by considering how you use data every day, discussing the value of data and examining the transformation of data from analogue to digital forms.

We will discuss and use case studies to understand the ethics of data usage, as well as the key role critical thinking plays in data analysis which ultimately drives strategic planning and informs corporate competitive advantage. All of this will culminate in the exploration of data, analysis tools and methodologies.

Whether you wish to move into a data analytics role, or are in the process of upskilling your data literacy to expand your current role, this course will enhance and solidify your ability to work with data in the workplace.

What you'll learn

After completing this course, learners will be able to:

● Give examples of how people use data every day

● Describe legal and ethical issues associated with data

● Apply critical thinking skills when working with data

● Identify appropriate data analysis tools and techniques for various needs

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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Covers legal issues associated with data, which is critical to understanding and mitigating risks in the field
Focuses on critical thinking as an essential skill for data analysis, a highly sought-after skill in today's job market
Taught by Beth Prince-Bradbury, who has extensive experience in data analytics and is recognized for her work in the field
Provides a foundation in data literacy, which is crucial for individuals seeking to enter or advance in the field of data analytics
Develops skills in identifying appropriate data analysis tools and techniques, empowering learners to effectively analyze data

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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 Foundations with these activities:
Review fundamental math skills
Strengthen foundational math skills to enhance comprehension of data analysis concepts.
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Show steps
  • Review basic arithmetic operations (addition, subtraction, multiplication, division)
  • Practice solving algebraic equations and inequalities
Explore case studies of successful data-driven decision-making
Gain insights into real-world applications of data analysis by examining case studies.
Show steps
  • Identify case studies relevant to your industry or domain
  • Analyze how data was used to inform decision-making
  • Evaluate the outcomes and impact of data-driven decisions
Explore Data Analysis Tutorials
Enhance your understanding of data analysis concepts by following guided tutorials and practicing with real-world datasets.
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Show steps
  • Identify reputable data analysis resources
  • Select tutorials that align with your skill level
  • Follow the instructions and complete the exercises
  • Experiment with different data analysis tools
Seven other activities
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Analyze data using statistical software
Gain proficiency in using statistical software to perform data analysis and extract insights.
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  • Learn the basics of statistical software (e.g., R, Python)
  • Practice importing and cleaning data
  • Apply statistical techniques (e.g., descriptive statistics, hypothesis testing)
Data Analysis Practice Problems
Reinforce your data analysis skills by solving practice problems and receiving immediate feedback.
Show steps
  • Find platforms or resources offering data analysis practice problems
  • Attempt to solve a variety of problems
  • Review your solutions and identify areas for improvement
  • Seek guidance from peers or instructors when needed
  • Regularly engage in practice to enhance your proficiency
Participate in peer review sessions for data analysis projects
Develop critical thinking and analytical skills by participating in peer reviews.
Show steps
  • Join or form a peer review group
  • Present and receive feedback on your own data analysis projects
  • Provide constructive criticism to peers
Attend Data Analytics Meetups
Connect with professionals in the field of data analytics to expand your network and gain insights.
Show steps
  • Research and identify relevant data analytics meetups
  • Attend the meetups and actively participate in discussions
  • Network with other attendees, speakers, and organizers
  • Stay engaged with the community by joining online forums or social media groups
Develop a data visualization dashboard
Enhance understanding of data visualization techniques and develop skills in creating interactive dashboards.
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  • Gather and prepare data for visualization
  • Use visualization tools (e.g., Tableau, Power BI) to create interactive dashboards
  • Present and interpret findings from the dashboard
Data Analytics Project
Apply your data analysis skills to a real-world project and demonstrate your abilities to potential employers or clients.
Show steps
  • Define the project scope and objectives
  • Gather and clean the necessary data
  • Analyze the data to extract insights
  • Develop recommendations or solutions based on the analysis
  • Present your findings and communicate your results effectively
Contribute to open source data analysis libraries or projects
Gain practical experience in data analysis and contribute to the community.
Show steps
  • Identify suitable open source data analysis projects or libraries
  • Review code and identify areas for improvement
  • Make code contributions or report issues

Career center

Learners who complete Data Literacy Foundations will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts build and analyze datasets to extract meaningful insights from data. They use data analysis tools such as SQL, Python, and R to clean, organize, and analyze data. A course in Data Literacy Foundations can help you develop the critical thinking skills necessary to succeed as a Data Analyst. You'll learn how to evaluate data sources, identify trends, and communicate your findings to stakeholders.
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior and market trends. The course in Data Literacy Foundations can help you develop the skills necessary to become a successful Market Researcher, by providing you with a foundation in data analysis and critical thinking. You'll learn how to design and conduct market research surveys, analyze data to identify trends, and present your findings to clients.
Data Scientist
Data Scientists use data analysis tools to extract meaningful insights from data. They use their findings to solve business problems and develop new products and services. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Data Scientist. You'll learn how to clean, organize, and analyze data, and how to use data analysis tools to extract meaningful insights.
Business Analyst
Business Analysts help businesses understand their data and make informed decisions. The skills you'll learn in the course, such as data analysis, critical thinking, and problem solving, will give you a competitive advantage in your role as a Business Analyst.
Financial Analyst
Financial Analysts use data to make investment decisions. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Financial Analyst. You'll learn how to analyze financial data, identify trends, and make sound investment decisions with the help of data analysis tools and techniques.
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency of operations. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Operations Research Analyst by teaching you how to analyze data to identify inefficiencies in procedures, and develop and implement solutions to improve processes.
Quantitative Analyst
Quantitative Analysts use data to make investment decisions. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Quantitative Analyst. You'll learn how to analyze financial data, identify trends, and make sound investment decisions with data analytics.
Risk Analyst
Risk Analysts use data to identify and mitigate risks. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Risk Analyst. You'll learn how to analyze data to identify risks, develop mitigation plans, and make informed decisions.
Data Engineer
Data Engineers design and build data pipelines and databases. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Data Engineer. You'll learn how to design and build data pipelines, work with databases, and use data analysis tools to extract meaningful insights from data.
Data Architect
Data Architects design data models and data management systems. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Data Architect. You'll learn how to design data models, build data management systems, and use data analysis tools to extract meaningful insights from data.
Database Administrator
Database Administrators manage and maintain databases. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Database Administrator. You'll learn how to manage and maintain databases, use data analysis tools to extract meaningful insights from data, and develop and implement data security measures.
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies and procedures. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Data Governance Analyst. You'll learn how to develop and implement data governance policies and procedures, and how to use data analysis tools to extract meaningful insights from data.
Data Privacy Analyst
Data Privacy Analysts develop and implement data privacy policies and procedures. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Data Privacy Analyst. You'll learn how to develop and implement data privacy policies and procedures, and how to use data analysis tools to extract meaningful insights from data.
Data Protection Officer
Data Protection Officers oversee the implementation of data protection policies and procedures. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Data Protection Officer. You'll learn how to develop and implement data protection policies and procedures, and how to use data analysis tools to extract meaningful insights from data.
Chief Data Officer
Chief Data Officers oversee the organization's data strategy and data governance. The course in Data Literacy Foundations will provide you with the skills necessary to become a successful Chief Data Officer. You'll learn how to develop and implement data strategy, data governance policies and procedures, and how to use data analysis tools to extract meaningful insights from data.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Literacy Foundations.
Provides a comprehensive guide to data science project design, from data collection to analysis and communication. It valuable reference for both beginners and experienced data scientists.
Provides insights into the real-world challenges and opportunities of data science. It offers practical advice and perspectives from experienced data scientists.
Explores the ethical implications of algorithms and AI. It provides a framework for designing and using algorithms that are fair, transparent, and accountable.
Demystifies statistics, making it accessible and engaging. It provides a solid foundation for understanding data and its analysis.
Combines probability and statistics with data analysis. It provides a hands-on approach to data exploration and modeling, using Python.
Provides a framework for critical thinking, which is an essential skill for data literacy. It helps readers to develop the skills they need to evaluate data, identify bias, and make sound judgments.
Provides a practical introduction to data visualization. It covers topics such as choosing the right charts and graphs, and how to use data visualization to communicate effectively.
Provides a comprehensive overview of data mining techniques. It valuable resource for anyone looking to learn how to use data mining to extract knowledge from data.
Provides a practical introduction to machine learning. It covers topics such as supervised learning, unsupervised learning, and ensemble methods.
Provides a comprehensive overview of deep learning. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.

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