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Data Literacy in Practice

Emily Pressman

In this course, you learn practical skills to explore and visualize data. You will follow a small business owner's data-driven journey to improve company performance to gain skills to prepare data, conduct analysis, and share insights using data visualizations. By the end of this course, you will be able to prepare data and conduct exploratory analysis, investigate relationships in the data by using visualizations, and communicate findings. If you are new to analyzing data, this course is for you. The focus in this course is on practical understanding while avoiding complicated statistical terminology to help you feel supported and encouraged throughout the process. Anybody can be successful in this course regardless or background.

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What's inside

Syllabus

Welcome to the Data Literacy: Exploring and Visualizing Data Specialization
In this module you learn about the scope and structure of the courses in this Data Literacy: Exploring and Visualizing Data Specialization.
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Data Literacy in Practice
In this course, you learn practical skills to explore and visualize data. You will follow a small business owner's data-driven journey to improve company performance to gain skills to prepare data, conduct analysis, and share insights using data visualizations. By the end of this course, you will be able to prepare data and conduct exploratory analysis, investigate relationships in the data by using visualizations, and communicate findings. If you are new to analyzing data, this course is for you. The focus in this course is on practical understanding while avoiding complicated statistical terminology to help you feel supported and encouraged throughout the process. Anybody can be successful in this course regardless or background.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops foundational data analysis skills, including preparing data, conducting exploratory analysis, and communicating findings through data visualizations
Suitable for beginners, focusing on practical understanding and avoiding complex statistical terminology
Intended for individuals with any background, making it accessible to a wide range of learners

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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 in Practice with these activities:
Read and review The Data Warehouse Toolkit
Introduce yourself to the key concepts, methodologies, and guidelines for best practices with this in-depth book.
Show steps
  • Read and analyze the book
  • Take notes and highlight important concepts
  • Complete the exercises and case studies
Compile a collection of resources on data literacy
Become a more well-rounded data literacy student by accessing a curated list of materials.
Browse courses on Data Literacy
Show steps
  • Search for resources on data literacy
  • Organize and categorize the resources
  • Create a document or website to share the compilation
Review basic statistical concepts and techniques
Strengthen your foundation by refreshing your knowledge of key statistical concepts and methods.
Browse courses on Statistics
Show steps
  • Review your class notes and textbooks
  • Take practice quizzes or mock exams
  • Watch online tutorials or videos
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow tutorials on using open-source data visualization tools
Explore and experiment with different data visualization options by utilizing beginner-friendly tutorials.
Browse courses on Data Visualization
Show steps
  • Search for tutorials on open-source data visualization tools
  • Choose a tool and follow the instructions
  • Practice creating visualizations with the tool
Design data visualizations using a tool like Tableau
Become more comfortable and proficient in using Tableau to explore and visualize data.
Browse courses on Data Visualization
Show steps
  • Install and familiarize yourself with Tableau
  • Attend an introductory workshop or tutorial
  • Practice creating different types of visualizations
  • Share your visualizations with others
Develop an infographic or presentation on a data analytics topic
Enhance your understanding and communicate your knowledge by creating a visual representation or presentation.
Browse courses on Data Analytics
Show steps
  • Choose a specific data analytics topic
  • Research and gather relevant data
  • Design and create your infographic or presentation
Solve data analysis and visualization problems on LeetCode
Challenge yourself with a curated collection of hands-on problems to improve your understanding.
Browse courses on Data Analysis
Show steps
  • Create a LeetCode account
  • Start solving easy-level problems
  • Work your way up to more challenging problems
Analyze and visualize a dataset of your choice
Demonstrate your ability to apply the skills you're learning in a practical setting.
Browse courses on Data Analysis
Show steps
  • Find or create a dataset
  • Clean and prepare your data
  • Perform exploratory data analysis and visualization
  • Make meaningful conclusions and insights

Career center

Learners who complete Data Literacy in Practice will develop knowledge and skills that may be useful to these careers:
Data Analyst
With the practical data exploration and visualization skills gained in this course, you will be well-equipped to begin a career as a Data Analyst. In this role, you will use your knowledge to translate raw data into insights that can guide business decisions and improve efficiency. The course's focus on avoiding complicated statistical terminology and providing practical understanding will give you a strong foundation for success in this field.
Business Analyst
The skills you'll develop in this course, such as data preparation, analysis, and visualization, are essential for success as a Business Analyst. You'll be able to use data to identify trends, patterns, and insights that can help businesses make better decisions. The course's emphasis on practical understanding without complicated statistical terminology will give you a competitive edge in this role.
Data Engineer
This course will provide you with a solid foundation for a career as a Data Engineer. You'll learn how to prepare and manage large datasets, as well as how to design and implement data pipelines. The course's emphasis on practical understanding will give you the skills you need to succeed in this technical role.
Data Scientist
The skills you'll gain in this course, such as data exploration, analysis, and visualization, are essential for success as a Data Scientist. You'll be able to use data to build predictive models and solve complex business problems. The course's focus on practical understanding without complicated statistical terminology will give you a strong foundation for a successful career in this field.
Machine Learning Engineer
This course will provide you with a solid foundation for a career as a Machine Learning Engineer. You'll learn how to build and deploy machine learning models, as well as how to evaluate their performance. The course's emphasis on practical understanding will give you the skills you need to succeed in this technical role.
Data Visualization Specialist
This course will provide you with the skills you need to become a Data Visualization Specialist. You'll learn how to create clear and concise data visualizations that can communicate insights effectively. The course's focus on practical understanding will give you the skills you need to succeed in this creative and technical role.
Market Researcher
The skills you'll develop in this course, such as data analysis and visualization, are essential for success as a Market Researcher. You'll be able to use data to understand consumer behavior and trends, and to make recommendations for marketing campaigns. The course's focus on practical understanding without complicated statistical terminology will give you a competitive edge in this role.
Financial Analyst
This course will provide you with a solid foundation for a career as a Financial Analyst. You'll learn how to analyze financial data and make recommendations for investment decisions. The course's emphasis on practical understanding will give you the skills you need to succeed in this technical role.
Risk Analyst
The skills you'll gain in this course, such as data analysis and visualization, are essential for success as a Risk Analyst. You'll be able to use data to identify and assess risks, and to make recommendations for risk mitigation strategies. The course's focus on practical understanding without complicated statistical terminology will give you a competitive edge in this role.
Operations Research Analyst
This course will provide you with a solid foundation for a career as an Operations Research Analyst. You'll learn how to use data to optimize business processes and make decisions. The course's emphasis on practical understanding will give you the skills you need to succeed in this technical role.
Quantitative Analyst
The skills you'll develop in this course, such as data analysis and visualization, are essential for success as a Quantitative Analyst. You'll be able to use data to build financial models and make investment decisions. The course's focus on practical understanding without complicated statistical terminology will give you a competitive edge in this role.
Actuary
This course will provide you with a solid foundation for a career as an Actuary. You'll learn how to use data to assess risk and make recommendations for insurance policies. The course's emphasis on practical understanding will give you the skills you need to succeed in this technical role.
Statistician
The skills you'll gain in this course, such as data analysis and visualization, are essential for success as a Statistician. You'll be able to use data to conduct research studies and draw conclusions. The course's focus on practical understanding without complicated statistical terminology will give you a competitive edge in this role.
Epidemiologist
This course will provide you with a solid foundation for a career as an Epidemiologist. You'll learn how to use data to investigate disease outbreaks and make recommendations for public health policies. The course's emphasis on practical understanding will give you the skills you need to succeed in this technical role.
Data Journalist
The skills you'll develop in this course, such as data visualization and communication, are essential for success as a Data Journalist. You'll be able to use data to tell stories and inform the public. The course's focus on practical understanding without complicated statistical terminology will give you a competitive edge in this role.

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 in Practice.
This classic book on data visualization provides a deep understanding of the principles and techniques of creating effective visualizations. It valuable reference for anyone who wants to learn more about the field.
Provides a comprehensive overview of data visualization techniques and best practices. It covers topics such as data exploration, visual perception, and creating effective visualizations.
Provides a comprehensive overview of data visualization techniques and best practices. It includes examples of effective data visualizations from a variety of industries and domains.
Provides a guide to using Pandas to manipulate and analyze data. It covers topics such as data cleaning, data exploration, and creating data visualizations.
Provides a comprehensive overview of the field of data literacy. It covers topics such as data collection, data analysis, and data visualization.
Provides a collection of recipes for solving common data analysis problems. It covers topics such as data cleaning, data exploration, and creating data visualizations.
Provides a practical guide to choosing the right charts and graphs for different types of data and audiences. It includes examples of effective data visualizations from a variety of industries.
Provides a guide to using Python and JavaScript to create interactive data visualizations. It covers topics such as data wrangling, creating charts and graphs, and building dashboards.
Provides a broad overview of the field of data science. It covers topics such as data mining, machine learning, and data ethics.
Provides a gentle introduction to data analysis and visualization for beginners. It covers topics such as data cleaning, exploratory data analysis, and creating basic visualizations.

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