Data Visualization with Python

Learn how scientists and engineers turn numbers into pictures and stories! In this fun, beginner-friendly course, with no software installation required, students will use Python libraries, NumPy and Matplotlib, in Google Colab to explore data, create beautiful graphs, and understand how computers see the world. Students will be provided templates in order to build real-world projects such as simulating quiz scores, tracking temperature data, or creating a face with math, all to prepare for a final project to tell their own data story.

Data Visualization with Python

What’s Included

Live Meetings

Total Meetings

10 Meetings - Includes 1 Lecture and 1 Guided Coding session per week

Homework

Projects

Due Weekly, based on in-class coding sessions and templates provided

Assessment

Assessment

No assessments as this is a project based course.

Certificate of Completion

Certification

Will be provided by PenguinLearn.

What You Will Learn

By the end of this course, students will: Understand how to create and use NumPy arrays for storing and manipulating data. Use Matplotlib to make line plots, bar charts, scatter plots, and histograms. Combine data and visuals to find patterns or tell a story. Customize plots with colors, labels, legends, and styles. Build a final “data story” visualization using what they have learned.

Syllabus

Intro to Data with Python

Intro to Google Colab and running code Importing libraries Basic Python math and lists Creating and using NumPy arrays Plotting your first graph with Matplotlib Homework: Make your first line plot of a dataset (i.e., screen time, daily steps, or a simple function).

Interpreting Data with NumPy

Generating random or evenly spaced data Computing mean, median, and standard deviation Combining arrays and reshaping data Visualizing arrays as points or patterns Homework: Simulate “quiz scores” and find the mean, median, and standard deviation as well as plot results as a bar and scatter chart.

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