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Artificial Intelligence

59 topics

How machines learn from data: models, neural networks and their use. All topics of the subject on YourAIZone. Open a topic to read the beginning of the lesson.

Artificial Intelligence — Explorer Level 7 topics

  1. Is AI a Person or a Helper?
  2. Spot the AI at Home
  3. AI or Just a Machine?
  4. Show Me Lots of Cats
  5. Good Examples, Bad Examples
  6. Guess the Next Word
  7. The Computer Guesses Too

Artificial Intelligence — Foundations 12 topics

  1. What Is Artificial Intelligence?
  2. A Short History of AI
  3. How Machines Learn: Data and Patterns
  4. Rules vs Learning: Two Ways to Program
  5. Types of Machine Learning
  6. Inside a Neural Network
  7. Computer Vision: How AI Sees
  8. Natural Language Processing: How AI Reads and Writes
  9. Large Language Models and Chatbots
  10. Generative AI: Creating Images, Music and Video
  11. AI Limitations: Hallucinations, Bias and Errors
  12. Using AI Responsibly

Machine Learning Fundamentals 12 topics

  1. The Machine Learning Workflow
  2. Data: The Fuel of ML
  3. Preparing Data: Cleaning, Scaling and Splitting
  4. Linear Regression: Predicting Numbers with a Line
  5. Classification Basics: k-NN and Logistic Regression
  6. Decision Trees and Random Forests
  7. Evaluating Models: Accuracy, Precision, Recall
  8. Overfitting and Underfitting
  9. Unsupervised Learning: Clustering with k-Means
  10. Features That Matter: Feature Engineering
  11. Reinforcement Learning Basics
  12. Your First ML Project: End to End

Neural Networks & Deep Learning 10 topics

  1. From Biological to Artificial Neurons
  2. The Perceptron and Activation Functions
  3. Multi-Layer Networks and Forward Propagation
  4. How Networks Learn: Loss Functions and Gradient Descent
  5. Backpropagation: The Intuition
  6. Training in Practice: Epochs, Batches and Learning Rate
  7. Convolutional Neural Networks: How Deep Nets See
  8. Recurrent Networks and Sequences
  9. Attention and the Transformer
  10. Embeddings: Representing Meaning as Vectors

Generative AI & Large Language Models 10 topics

  1. What Is Generative AI?
  2. How LLMs Work: Tokens and Next-Word Prediction
  3. How LLMs Are Trained: Pretraining, Fine-Tuning, RLHF
  4. Prompt Engineering Basics
  5. Advanced Prompting Techniques
  6. Hallucinations: Why LLMs Make Things Up
  7. Giving AI Your Documents: RAG
  8. AI Agents: Models That Use Tools
  9. Image, Audio and Video Generation
  10. Building with AI: APIs and the Ecosystem

AI Ethics & Society 8 topics

  1. Why AI Ethics Matters
  2. Bias in AI Systems
  3. Privacy and Your Data
  4. Deepfakes and Misinformation
  5. AI and Jobs: Automation and New Professions
  6. AI in High-Stakes Decisions: Medicine, Law and Money
  7. AI Safety and Alignment
  8. Rules for AI: Regulation and Responsible Use

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