A program curated for middle school students to learn the fundamentals of python and key concepts in machine learning and artificial intelligence. Work on hands-on group projects.

AI Trailblazers

A program curated for middle school students to learn the fundamentals of Python and key concepts in Machine Learning and Artificial Intelligence. Build real world AI models across fields!

AI Trailblazers

Program Structure

Weeks 1 & 2:

Build a foundation in AI & ML and learn about data analysis

Weeks 3 & 5:

Receive an introduction to key topics in AI - including exploratory data analysis, regression, and classification problems

Weeks 6 & 10:

Deep dive into some more complex topics which includes:

  • Image Classification

  • Neural Networks 

  • Why AI Ethics Matter

Program Structure

Weeks 1 to 2:

Build a foundation in AI & ML and learn about data analysis

Weeks 3 to 5:

Receive an introduction to key topics in AI - including exploratory data analysis, regression, and classification problems

Weeks 6 to 10:

  • Image Classification

  • Neural Networks 

  • Why AI Ethics Matter

Deep dive into some more complex topics which includes:

Program Details

This program is conducted entirely online!

  • 25 hours over 10 weeks (weekends) OR 25 hours over 2 weeks (weekdays on summer break).

  • Section lectures for 1.5 hours and group session with a 5:1 student to mentor ratio for 1 hour (total: 2.5 hours per session)

  • None!

  • Grades 6-8

  • A group project with 3-4 other students

Here is the program brochure with more details!

Program Details

This program is conducted entirely online!

  • 25 hours over 10 weeks (weekends) OR 25 hours over 2 weeks (weekdays during the summer).

  • Section lectures for 1.5 hours and group session with a 5:1 student to mentor ratio for 1 hour (total: 2.5 hours per session)

  • None!

  • Grades 6-8

  • A group project with 3-5 other students.

Here is the program brochure with more details!

AI Trailblazers Course Syllabus

Session 1
Session 2
Session 3
Session  4
Session 5
Session 6
Session 7
Session 8
Session 9
Session 10
Lecture 1: Theory
Introduction to AI and ML
Exploratory Data Analysis (EDA)
Data, Regression Problems, Linear Regression
Multiple Regression
Classification Problems, Logistic Regression
Introduction to Neural Networks (NNs)
Tuning Neural Networks
Introduction to Convolutional Neural Networks (CNNs)
AI Ethics
Project: Presentation Practice
Lecture 2: Interactive Coding
Intro to Python & Basic Programming
Intro to Python & Basic Programming
EDA
Linear Regression and Multiple Regression
Logistic Regression
Neural Networks
More Practice with Neural Networks
CNNs
Project: Model Evaluation
Presentation and Closing Ceremony
Hands-on Session: Small Group
Hands-on work
Hands-on work
Hands-on work
Hands-on work
Hands-on work
Project: Research Question and EDA!
Project: Model Training
Project: Model Training
Project: Presentation Prep
Feedback Discussion

AI Trailblazers Course Syllabus

Lecture 1:

Theory

Introduction to AI and ML

Session 1

Exploratory Data Analysis (EDA)

Session 2

Data, Regression Problems, Linear Regression

Session 3

Multiple Regression

Session 4

Classification Problems, Logistic Regression

Session 5

Introduction to Neural Networks (NNs)

Session 6

Tuning Neural Networks

Session 7

Introduction to Convolutional Neural Networks (CNNs)

Session 8

Lecture 2:

Interactive Coding

Intro to Python & Basic Programming

Intro to Python & Basic Programming

EDA

Linear Regression and Multiple Regression

Logistic Regression

Neural Networks

More Practice with Neural Networks

CNNs

Project: Model Evaluation

Presentation and Closing Ceremony

Hands-on Session:

Small Group

Hands-on work

Hands-on work

Hands-on work

Hands-on work

Hands-on work

Project: Research Question and EDA!

Project: Model Training

Project: Model Training

Project: Presentation Prep

Feedback Discussion

AI Ethics

Session 9

Project: Presentation Practice

Session 10