Data Science and AI Project Program

Prepare your child for the future of STEM with our Data Science & AI Project Program, where students go beyond theory and learn how to actually build with data and artificial intelligence.

Students develop a strong foundation in Python programming, data science, and machine learning through structured, hands-on, guided projects designed to build real problem-solving ability.

Step by step, they learn how to analyze data, uncover patterns, and develop AI-based solutions to meaningful problems.

This program is carefully designed to develop the skills, confidence, and independent thinking needed to succeed in Canada-Wide Science Fairs and AI competitions, while also building a strong foundation for future studies in computer science, engineering, and AI.

Data Science and AI Program Curriculum

Python for Data Science

Python programming fundamentals (variables, loops, functions)
Working with libraries (NumPy, pandas, matplotlib)
Reading and handling datasets (CSV files)
Data cleaning and preprocessing

Data Science Fundamentals

Types of data (numerical, categorical)
Descriptive statistics (mean, median, variance, distribution)
Data visualization and interpretation
Identifying patterns and trends in data

Introduction to Machine Learning

What is machine learning?
Types of ML
Supervised learning (Regression, Classification)
Unsupervised learning (intro level)
Features and labels
Training vs testing data
Overfitting vs underfitting
Model performance intuition

Machine Learning Workflow

Problem definition
Data collection and preparation
Feature selection
Model selection
Training the model
Testing and validation
Evaluation metrics (accuracy, error, etc.)
Iteration and improvement
Model explainability

Machine Learning Models

Linear regression (prediction)
Logistic regression (classification)
Decision trees (introduction)
Basic clustering concepts

Three Guided Projects

Stock price prediciton
Disease classification
Student's choice

Communication & Presentation Skills:

Explaining AI models in simple language
Presenting findings clearly
Writing structured project reports
Building confidence in explaining technical work

Tools used:

Python
Google Colab
pandas
NumPy

Duration:

5 - 6 months

Outcomes:

Code confidently in Python for data tasks
Understand how machine learning works end-to-end
Build and evaluate simple AI models
Complete guided AI projects with structure and clarity
Develop strong foundations for advanced AI and competition training