Data Science 1

Description

Explore data in areas such as science, sports, politics, climate change, and much more!

Data is everywhere around us, transforming our world. The applications are countless: the world of Moneyball and sports statistics, archeologists discovering hidden civilizations with LiDAR data, climate scientists tracking temperature change and polar ice melt—data science and our data-driven world are bringing exciting insights, discoveries, and analysis to bear in almost every field imaginable.

In this introductory course, students will learn how to interrogate a data set, just like a data pro, then make their own conclusions. Students will:

• Learn how to make use of Python, the most popular language for data science
• Understand different types of data (categorical vs. numerical) as well as statistical analysis
• Model how things work, using data! Make a prediction, then test the results
• Create their own, original graphs and visualizations
• Learn the strengths and weaknesses of different visualization types: And how to filter, clean, and interpret data
• Apply basic statistical concepts like mean, median, mode, and standard deviation
• Learn the industry-standard Data Science libraries: numpy, pandas, and matplotlib

Whether they're curious about data journalism, science, or just want to tell a story with data, this course is a fast and fun way to get started. Learn more about becoming a Data Scientist, sometimes called "America's Hottest Job," and explore a variety of real-world, hands-on labs.

Previous Python programming experience is recommended but not strictly necessary (complete Tynker's Python 101, or Tynker's AP CS Principles). The only prerequisite is Algebra 1.