## Introductory Math

Check out these Khan Academy modules to review the computational skills you’ll need to get started working with data.

- Arithmetic: Review basic math tips and tricks for working with negative numbers, fractions, and decimals.
- Pre-algebra: Learn about ratios, equations, scientific notation, and ways to represent data.

## Algebra

Ready to work with variables? Dive into the following algebra topics important in data science.

- Algebra basics: Review equations, inequalities, and polynomials.
- Algebra 1: Work with functions, solve systems of equations, and factor quadratics.
- Algebra 2: Perform operations on polynomials, interpret exponential models, and learn about logarithms and function transformations.

## Introduction to Data

- IBM OpenDS4All Introduction: What is Data Science?
- A Gentle Introduction to Data Science: Talk by Marc Garcia
- Types of Data: Produced by Ahmed Gomaa, Associate Professor at University of Scranton and NSDC member.

- Analyzing categorical data: Read bar graphs, Venn diagrams, and two-way tables.
- Displaying and comparing quantitative data: Graph and compare distributions of quantitative data.
- Summarizing quantitative data: Measure central tendency using mean, median, and mode and variability with standard deviation and interquartile range.
- Full Data Science Course for Beginners by freeCodeCamp.org