**A 7.5 hour bootcamp spread over 5 days****,** where students learn data science by building and analyzing games! Data scientists apply maths and code to help people answer questions, solve problems, and build smarter applications.
Strive's Data Science Bootcamp takes middle school students from having no coding experience to applying Google's machine learning toolkit using the same maths they're learning in class.

Strive students learn to code in Python, one of the most useful programming languages in the world. They use the same coding environments as the pros: Jupyter notebooks for number crunching and p5 sketches for creative expression.

# 1. Data Visualization

A picture is worth a thousand words. Students begin their journey into data science by visualizing datasets that help them to form strategies for their favorite video games.

**Maths Outcomes**

- Variables
- Types of data
- Plotting

**Code Outcomes**

- Variables
- pandas DataFrames
- Bokeh plots

# 2. Seeing Statistics

Sometimes it's hard to see the forest for the trees. Students will learn how to apply appropriate summary statistics as they explore datasets from popular video games such as FIFA '21.

**Maths Outcomes**

- Mean, median, mode
- Extrema (max and min)
- Range

**Code Outcomes**

- Advanced DataFrames

# 3. Web Scraping

We rely upon websites for all sorts of information. Students will learn how to analyze them quickly as they explore video game sales data and stats from popular games.

**Maths Outcomes**

- Set Theory
- Time Series

**Code Outcomes**

- HTML
- Data Wrangling

# 4. Probability

What are the odds? Students will learn the rules of probability by building and studying games of chance that they can play with their friends.

**Maths Outcomes**

- Counting
- Rules of probability
- Probability distributions

**Code Outcomes**

- if statements
- Loops
- p5.js

# 5. Machine Learning

The AI age is upon us. Students will learn how maths and code drive the software that they love by building a sandworm game driven by Google's machine learning library.

**Maths Outcomes**

- Image Classification
- Sound Classification
- Coordinate Geometry

**Code Outcomes**

- Functions
- Teachable Machine
- ml5.js