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

Course

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.

Enroll Now

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

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.
2. Design of Visualizations
  Interpret features in terms of level of measurement and know different encodings that can be used to depict data in visualizations.
3. Univariate Exploration of Data
  Use bar charts to depict distributions of categorical variables.
4. Bivariate Exploration of Data
  Use scatterplots to depict relationships between numeric variables.
5. Multivariate Exploration of Data
  Use encodings like size, shape and color to encode values of a third variable in a visualization.
6. 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.
7. Visualization Case Study
  Apply your knowledge of data visualization to a dataset involving the characteristics of diamonds and their prices.
8. 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.
- 59%
  of companies plan to increase positions requiring data analysis skills.

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.

Experienced Project Reviewers
Real-Time Support

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.

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.