Course

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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  • DAYS
  • HRS
  • MIN
  • SEC
  • Estimated Time
    16 hours

  • Enroll by
    September 22, 2021

    Get access to classroom immediately on enrollment

  • Prerequisites
    Basic Python skills, statistics and probability concepts

What You Will Learn

Syllabus

Data Visualization

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.

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.

  • 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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59%

of companies plan to increase positions requiring data analysis skills.

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Data Visualization

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  • Monthly Access

    Pay as you go


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    • Maximum flexibility to learn at your own pace.
    • Cancel anytime.
  • Learn

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

    On average, successful students take 16 hours to complete this program.
  • Benefits include

    • Real-world projects from industry experts
    • Technical mentor 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 course is comprised of content and curriculum to support one project. We estimate that students can complete the program in 16 hours.

    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

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