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Che Smith

Learn data literacy online using R programming

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Learn data literacy online using R programming

What is data literacy and why is it important? In this data literacy course, you will learn how to become data literate. This will be accomplished by performing data analysis, data visualization, and communicating with data, using real datasets and examples that are relevant to a variety of audiences and academic disciplines. Data is part of every field, but not everyone has had the opportunity to gain the skills necessary to find the data they need and use it in ways that add to their work. Whether you are in public health, healthcare, banking, law, education, graduate school, or a variety of other fields, there is a way to understand and make use of related data.

Earn your data literacy certificate online

This free four-week course will give you the opportunity to build and leverage your data skills for upward mobility at any stage in your career. It will take you through the six steps of the data lifecycle, using different case studies and contexts, and teach you how to analyze, manage, and communicate data, working in R to achieve basic R programming competencies. R is a statistical programming language that is a great resource to analyze data, manage data, and visualize data.

No experience is required to learn this in-demand skill. By the end of this data literacy training course, you will be able to identify key principles of data analysis, use critical thinking skills, and become proficient in building powerful visuals. If you are interested in building a career in data analytics, first learning these foundational lessons is vital.

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What's inside

Learning objectives

  • The six steps of the data lifecycle
  • Develop your data analytics skills
  • Use r to perform probability functions, statistical analysis, data management, and more
  • Learn how to be a critical consumer and producer of data visualizations
  • Gain a deeper understanding of your company’s data needs
  • Discover how to market your data skills to employers

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Matches core skills for data analysts
Taught by recognized expert(s) in field
Provides solid foundational knowledge
Uses a mix of media for a better learning experience
Teaches tools and skills relevant in industry

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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 The Essentials of Data Literacy Online Course with these activities:
Practice basic R programming on HackerRank
Develop fluency with R programming syntax and techniques through repetitive practice.
Browse courses on R Programming
Show steps
  • Create an account on HackerRank.
  • Solve the 'Basic R Programming' problems.
  • Check your solutions and learn from the provided feedback.
Follow a Codecademy course on Data Analysis with R
Gain practical experience in performing data analysis tasks using R.
Browse courses on Data Analysis
Show steps
  • Create an account on Codecademy.
  • Enroll in the 'Data Analysis with R' course.
  • Complete the interactive lessons and coding challenges.
Create data visualizations using R
Develop skills in communicating insights from data through effective visualizations.
Browse courses on Data Visualization
Show steps
  • Install the 'ggplot2' package in R.
  • Create a dataset for visualization.
  • Use ggplot functions to create different types of visualizations (e.g., line charts, bar charts, histograms).
Three other activities
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Participate in a DataCamp competition
Challenge yourself and apply your data literacy skills in a competitive environment.
Browse courses on Data Analysis
Show steps
  • Create an account on DataCamp.
  • Join a competition that aligns with your interests.
  • Use the provided resources and your R skills to solve the competition tasks.
Volunteer as a mentor or tutor in R or data analytics
Reinforce your understanding by teaching others and contribute to the community.
Browse courses on Mentoring
Show steps
  • Identify opportunities for volunteering as a mentor.
  • Prepare materials and resources to support your mentees.
  • Provide regular guidance and feedback to help them develop their skills.
Organize and review your notes and course materials
Enhance your retention and understanding by organizing and revisiting key concepts.
Show steps
  • Gather all notes, assignments, quizzes, and exams.
  • Create a logical filing system for easy retrieval.
  • Periodically review your materials to refresh your memory and reinforce learning.

Career center

Learners who complete The Essentials of Data Literacy Online Course will develop knowledge and skills that may be useful to these careers:
Statistician
A Statistician collects, analyzes, and interprets data to provide insights and recommendations to organizations. This course may be useful for aspiring Statisticians, as it provides a foundation in data analysis and data visualization.
Data Scientist
A Data Scientist uses their knowledge of mathematics, statistics, and computer science to extract insights from data to solve business problems. This course may be helpful for aspiring Data Scientists, as it provides a foundation in data analysis, data management, and data visualization using R programming.
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to solve business problems. This course may be useful for aspiring Operations Research Analysts, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating operational data.
Data Analyst
A Data Analyst collects, analyzes, and interprets data to provide insights and recommendations to organizations. This course may be useful for aspiring Data Analysts, as it provides a foundation in data analysis, data management, and data visualization.
Database Administrator
A Database Administrator manages and maintains databases to ensure that data is available and secure. This course may be useful for aspiring Database Administrators, as it provides a foundation in data management.
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations. This course may be useful for aspiring Financial Analysts, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating financial data.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines to ensure that data is available for analysis. This course may be useful for aspiring Data Engineers, as it provides a foundation in data management and data visualization.
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical techniques to analyze financial data. This course may be useful for aspiring Quantitative Analysts, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating financial data.
Actuary
An Actuary uses mathematical and statistical techniques to assess risk and uncertainty. This course may be useful for aspiring Actuaries, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating risk and uncertainty.
Epidemiologist
An Epidemiologist investigates the causes and spread of disease. This course may be useful for aspiring Epidemiologists, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating epidemiological data.
Biostatistician
A Biostatistician applies statistical methods to solve problems in the field of biology. This course may be useful for aspiring Biostatisticians, as it provides a foundation in data analysis and data visualization.
Market Researcher
A Market Researcher conducts research to gather information about target markets, their needs, and their preferences. This course may be useful for aspiring Market Researchers, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating market research data.
Public Health Analyst
A Public Health Analyst uses data to improve public health outcomes. This course may be useful for aspiring Public Health Analysts, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating public health data.
Health Informatics Specialist
A Health Informatics Specialist uses data to improve healthcare delivery. This course may be useful for aspiring Health Informatics Specialists, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating healthcare data.
Business Analyst
A Business Analyst identifies and analyzes business requirements, and then develops solutions to improve business operations. This course may be useful for aspiring Business Analysts, as it provides a foundation in data analysis and data visualization, which are essential skills for understanding and communicating business needs.

Reading list

We've selected ten 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 The Essentials of Data Literacy Online Course.
Comprehensive guide to using R for data science. It covers everything from data cleaning and exploration to statistical modeling and machine learning. It valuable reference for anyone who wants to learn how to use R for data analysis.
Gentle introduction to machine learning. It covers the basics of machine learning, including supervised learning, unsupervised learning, and reinforcement learning. It great book for beginners who want to learn more about machine learning.
Practical guide to using data science for business. It covers everything from data collection and exploration to statistical modeling and machine learning. It valuable reference for anyone who wants to learn how to use data science to improve their business.
Practical guide to data visualization. It covers the basics of data visualization, including how to choose the right chart type, how to design effective charts, and how to present data effectively. It valuable reference for anyone who wants to learn more about data visualization.
Comprehensive guide to statistical methods for data analysis. It covers everything from descriptive statistics to inferential statistics. It valuable reference for anyone who wants to learn more about statistical methods.
Thought-provoking exploration of the ethical and social implications of data science. It must-read for anyone who wants to understand the potential benefits and risks of data science.
Comprehensive guide to big data. It covers everything from big data architecture to big data analytics. It valuable reference for anyone who wants to learn more about big data.
Comprehensive guide to Hadoop. It covers everything from Hadoop architecture to Hadoop programming. It valuable reference for anyone who wants to learn more about Hadoop.
Comprehensive guide to Spark. It covers everything from Spark architecture to Spark programming. It valuable reference for anyone who wants to learn more about Spark.
Comprehensive guide to deep learning. It covers everything from deep learning architecture to deep learning programming. It valuable reference for anyone who wants to learn more about deep learning.

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