Machine learning fundamentalsSupervised learning: Learning from tagged instancesUnsupervised learning: uncovering latent structuresReinforcement learning: Mastering through experimentationFalse positive, false negative, true positive, true negativeUnderstanding neural networks and deep learningThe neuron: the basic building blockConnecting neurons: Layers and networksConnections and weightsThe learning processIntroduction to large language models (LLMs)What makes LLMs so powerful?Interacting with LLMs: The art of prompt engineeringKey parameters for LLM interactionsTokens and tokenizationHow tokenization worksBest practices for using LLMsInteracting with AI modelsSummary