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High School Foundations of Machine Learning

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The purpose of this course is to provide students with core foundational knowledge to deepen understanding of machine learning (ML) practices and applications. This course builds understanding of the mathematical foundation needed to create algorithms for use in artificial intelligence and machine learning. The content includes, but is not limited to, foundational knowledge and skills related to computer coding and software development.

Segment One

Module 01 – Trained for Success


·      Back to Basics

·      Data Visualization

·      Searching for Answers

·      Reasoning and Representation

·      Humans vs. Machines


Module 02 – Pursuit of Knowledge


·      Supervised Learning

·      It’s Classified

·      Unsupervised Learning

·      A Closer Look at Clustering

·      Reinforcement Learning

·      Comparison of Learning Models

·      Neural Networks


Module 03 – Trending Data


·      Data is in the Details

·      Functions and Algorithms

·      Models and Algorithms

·      Solving Problems

·      Training Datasets

·      Sources of Data


Segment Two

Module 04 – Crafty Calculations


·      Data Exploration

·      Data Management

·      Analyzing Data

·      Dark Side of Data

·      Data Relationships


Module 05 – Modeling Intelligence


·      Create a Model

·      Adjusting the Model

·      AI Answers

·      Modeling for Good

·      Computer Hardware

·      Architecture


Module 06 – Evaluating Solutions


·      Humans in the Loop

·      Fairness in AI

·      Bias in AI

·      Goals of AI

·      AI Solutions

·      Safe Development