AI & Machine Learning
Explore how computers learn from data, recognize patterns, and make predictions. These projects help students investigate training models, analyzing datasets, and understanding how artificial intelligence works in everyday technology.
Pattern Recognition
- Train a simple model to recognize shapes or colours
- Build a program that detects repeating patterns in numbers
- Compare human vs. computer accuracy in pattern tasks
Image Classification
- Use a beginner‑friendly tool to classify images (animals, objects)
- Test how dataset size affects accuracy
- Compare different image preprocessing methods
Sound & Speech Recognition
- Train a model to recognize simple sounds (claps, whistles)
- Compare accuracy with different microphones
- Test how background noise affects recognition
Predictive Models
- Build a program that predicts weather trends using past data
- Train a model to predict sports scores or outcomes
- Compare different algorithms for prediction accuracy
Neural Network Basics
- Visualize how a neural network processes information
- Test how changing layers or nodes affects performance
- Train a tiny neural network to solve a simple problem
Data Labeling & Bias
- Investigate how mislabeled data affects model accuracy
- Explore bias in datasets and how it impacts results
- Compare model performance with balanced vs. unbalanced data
Ethical AI
- Study how AI makes decisions and where errors occur
- Investigate privacy concerns in everyday AI tools
- Design guidelines for safe and responsible AI use
Real‑World Applications
- Build a simple recommendation system (movies, books)
- Create an AI model that helps organize homework or schedules
- Test how AI can assist with environmental monitoring
