AI Basics

Master the fundamental concepts of artificial intelligence with this interactive learning path.

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Core Concepts

What is Artificial Intelligence?

AI is a branch of computer science where machines demonstrate human-like intelligence through learning, reasoning, and self-correction.

AI Overview

Machine Learning Fundamentals

ML systems improve automatically through experience, using algorithms to parse data, learn patterns, and make decisions.

ML Diagram

Deep Learning Essentials

Neural networks with multiple layers enable systems to extract higher-level features from raw input data.

Neural Networks

AI Ethics Framework

Understand bias mitigation, privacy concerns, and ethical deployment of AI systems in real-world environments.

AI Ethics

Real-World Applications

AI transforms industries from healthcare diagnostics to autonomous driving through pattern recognition and predictive analytics.

Healthcare

Medical imaging analysis, drug discovery, and predictive diagnostics

Finance

Fraud detection, algorithmic trading, and risk assessment

Industry

Predictive maintenance, supply chain optimization, quality control

Quick Quiz

What is supervised learning?

A ML method where models learn patterns from labeled training datasets, mapping inputs to correct outputs through feedback.

Explain overfitting

When an ML model learns the training data too well, capturing noise instead of underlying patterns, leading to poor generalization.

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