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Data Visualization


Discover how data visualization can communicate insights far more effectively than text or tables. In this course, you’ll learn how to build data visualizations programmatically using Python, and how you can use visualization to both discover and convey trends in your data.

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  • Estimated time
    16 hours

  • Enroll by
    October 12, 2022

    Get access to classroom immediately on enrollment

  • Prerequisites
    Basic Python skills, statistics and probability concepts

What You Will Learn

  1. Data Visualization

    16 hours to complete

    Data visualization allows us to instantly see patterns in data that would otherwise be impossible to detect. Without visualization, humans would be unable to make sense of even small amounts of data, let alone the trillions of megabytes now generated every day. In this course, you’ll learn how to create illuminating charts of your data analyses, so you can convey findings to others in the most impactful way possible.

    Prerequisite knowledge

    1. Data Visualization in Data Analysis

      Understand why visualization is important in the practice of data analysis and know what distinguishes exploratory analysis from Explanatory analysis and the role of data visualization in each.

      • Design of Visualizations

        Interpret features in terms of level of measurement and know different encodings that can be used to depict data in visualizations.

        • Univariate Exploration of Data

          Use bar charts to depict distributions of categorical variables.

          • Bivariate Exploration of Data

            Use scatterplots to depict relationships between numeric variables.

            • Multivariate Exploration of Data

              Use encodings like size, shape and color to encode values of a third variable in a visualization.

              • Explanatory Visulizations

                Understand what it means to tell a compelling story with data and choose the best plot type, encodings and annotations to polish your plots.

                • Visulization Case Study

                  Apply your knowledge of data visualization to a dataset involving the characteristics of diamonds and their prices.

                  • Course Project: Communicate Data Findings

                    Real-world data rarely comes clean. Using Python, you’ll gather data from a variety of sources, assess its quality and tidiness, then clean it. You’ll document your wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations using Python and SQL.


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                  All our programs include:

                  • Real-world projects from industry experts

                    With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

                  • Technical mentor support

                    Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

                  • Workspaces

                    Validate your understanding of concepts learned by checking the output and quality of your code in real-time.

                  • Flexible learning program

                    Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

                  Course offerings

                  • Class content

                    • Real-world projects
                    • Project reviews
                    • Project feedback from experienced reviewers
                  • Student services

                    • Technical mentor support
                    • Student community

                  Succeed with personalized services.

                  We provide services customized for your needs at every step of your learning journey to ensure your success.

                  Get timely feedback on your projects.

                  • Personalized feedback
                  • Unlimited submissions and feedback loops
                  • Practical tips and industry best practices
                  • Additional suggested resources to improve
                  • 1,400+

                    project reviewers

                  • 2.7M

                    projects reviewed

                  • 88/100

                    reviewer rating

                  • 1.1 hours

                    avg project review turnaround time

                  Mentors available to answer your questions.

                  • Support for all your technical questions
                  • Questions answered quickly by our team of technical mentors
                  • 1,400+

                    technical mentors

                  • 0.85 hours

                    median response time

                  Learn with the best.

                  Learn with the best.

                  • Josh Bernhard

                    Data Scientist at Nerd Wallet

                    Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.

                  • Mike Yi

                    Data Analyst Instructor

                    Mike is a content developer with a multidisciplinary academic background, including math, statistics, physics, and psychology. Previously, he worked on Udacity's Data Analyst Nanodegree program as a support lead.

                  Data Visualization

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                  Data Visualization

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