Neural Networks, Machine Learning, and Data
Now that you can code, let's dive deep into how AI actually works! You'll explore neural networks (inspired by human brains), understand different types of machine learning, and learn about the critical role of training data. This is where you truly understand the science behind AI!
Explore the brain-inspired architecture of neural networks! Learn about neurons, layers, weights, and how information flows through a network to make predictions.
Start Session 4 →Learn the three main types: supervised learning (learning from examples), unsupervised learning (finding patterns), and reinforcement learning (learning through rewards)!
Start Session 5 →Understand why quality training data matters so much. Explore how biased data can lead to biased AI, and why diversity in training data is critical!
Start Session 6 →Big Idea: AI systems work by learning patterns from training data. Neural networks mimic biological brains to find these patterns, but the quality and diversity of training data directly affects how fair and effective the AI becomes!