Mathematics and Statistics for Machine Learning and Data Science

"Math Meets Machine: High School Data Science Essentials 📊✖️➗

Step into the world of numbers and algorithms with our High School Data Science course, tailored to prepare you for the ChatGPT and Generative AI revolution!

This course is inspired from the renown lesson from Stanford University that has over 100,000 students enrolled

What is this course about?

Embark on a voyage into the heart of data science with our dynamic curriculum, designed specifically for students to navigate the vast seas of data. Utilizing complimentary tools like Google Sheets, Python, and Data Commons, our learners will transform into data detectives, unraveling mysteries in project-centered learning modules. They will cultivate a deep-rooted comprehension of data analysis, the art of sampling, the intricate dance between correlation and causation, as well as the concepts of bias, uncertainty, and probability. Students will hone their skills in modeling with data, crafting and critiquing data-driven arguments, recognizing the influential role of data in our society, and beyond

Topics Covered

Episode 1

Variability, data and models
Data Science inquiry
Univariate, bivariate and multivariate data
Creating visual representations
Data cleaning

Episode 2

Using measures of center and spread to model data
Distributions and normal distributions
Sampling and variability
Probabilistic thinking

Episode 3

Linear regression and bivariate data
Using probability to analyze the fit of a regression
Spurious correlations, confounding and mediating variables
Make connections between the trend and the context to make predictions

Episode 4

Algorithmic Thinking
Basics Programming
Simulation
Variability
Theoretical and Experimental Probability
Conditional Probability

Episode 5

Foundations in Linear Algebra
Introduction to clustering
Two-way tables

Episode 6

Model Bias
Normalization and weighting of data
Forming mathematical models
Sensitivity analysis

Episode 7

Predictive modeling
Linear Algebra
Conditional Probability

Episode 8

Gathering and organizing data
Modeling
Analyzing and synthesizing

Data Science Portfolio

We're passionate about project-based learning, and we're confident that the following projects will spark inspiration and ignite a love for hands-on learning!