Generative AI and Large Language Models

21 lessons in AI Fundamentals

• Foundation Models vs Task-Specific ModelsSlides / Video
• Limitations, Bias, and Ethics of LLMsSlides / Video
• Context Window and Its LimitationsSlides / Video
• Zero-Shot, One-Shot, Few-Shot LearningSlides / Video
• Prompting and Prompt Engineering BasicsSlides / Video
• Reinforcement Learning from Human FeedbackSlides / Video
• Fine-Tuning and Instruction TuningSlides / Video
• Pretraining on Large Text CorporaSlides / Video
• Next-Token Prediction and Autoregressive GenerationSlides / Video
• Embeddings in LLMsSlides / Video
• Tokens and Tokenization in LLMsSlides / Video
• Self-Attention Mechanism IntuitionSlides / Video
• The Transformer Architecture OverviewSlides / Video
• What a Large Language Model IsSlides / Video
• Generative vs Discriminative AISlides / Video
• Real-World Applications of LLMsSlides / Video
• Generative Models Beyond TextSlides / Video
• Model Parameters and Scaling LawsSlides / Video
• Retrieval-Augmented Generation (RAG)Slides / Video
• Hallucinations and Factual ReliabilitySlides / Video
• Decoding: Temperature, Top-k, Top-pSlides / Video