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.
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
Stay Connected with Us
Email us at email@example.com with any inquiries or questions.
Some ways to stay connected with the NSDC community:
- Join our Slack channel
- Follow us on Twitter, Instagram, or LinkedIn
- Subscribe to the Northeast Hub YouTube channel
- Sign up for our NSDC mailing list
- Check out the REAL Volunteer Program for more collaboration opportunities