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Data Visualization with Python


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
    1 month

  • Enroll by
    June 7, 2023

    Get access to classroom immediately on enrollment

  • Skills acquired
    Exploratory Data Analysis, Data Visualization Design, Data Storytelling

What You Will Learn

  1. Data Visualization with Python

    1 month 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

    Basic Python skill, statistics and probability concepts.

    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 Visualizations

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

                • Visualization 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.

                  All Our Courses 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.

                  • Real-time support

                    On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.

                  • 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

                    • Student community
                    • Real-time support

                  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

                  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 with Python

                  Get started today

                    • Learn

                      How to build clear, impactful data visualizations using Python’s Matplotlib library.

                    • Average Time

                      On average, successful students take 1 month to complete this program.

                    • Benefits include

                      • Real-world projects from industry experts
                      • Real-time support

                    Program Details

                    • Do I need to apply? What are the admission criteria?

                      No. This Course accepts all applicants regardless of experience and specific background.

                    • What are the prerequisites for enrollment?

                      A well-prepared student should:

                      • Be able to use Anaconda to manage packages and environments for use with Python
                      • Be able to use Jupyter notebook to combine explanatory text, math equations, code, and visualizations in one sharable document
                      • Have basic Python skill: use NumPy and Pandas to wrangle, explore, analyze, and visualize data
                      • Be familiar with basic statistics and probability concepts such as linear regression, the normal distribution
                    • How is this course structured?

                      The Data Visualization with Python course is comprised of content and curriculum to support one project. We estimate that students can complete the program in 1 month.

                      The project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.

                    • How long is this course?

                      Access to this course runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our programs.

                    • Can I switch my start date? Can I get a refund?

                      Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.

                    • What software and versions will I need in this course?

                      You will need access to the Internet, and a 64 bit computer. Additional software such as Python and its common data analysis libraries (e.g., Numpy and Pandas) will be required, but the program will guide students on how to download once the course has begun.

                    Data Visualization with Python

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