AI Fundamentals: From Basics to Generative AI

Explore how AI and smart machines integrate into everyday life, from fraud detection and SEO optimization to healthcare predictions and autonomous driving.

Reflect on AI's evolving capabilities and limitations, explore benefits and risks, and consider ethical responsibilities as AI reshapes daily life, industries, jobs, and the skills valued in work.

Explore how we train ai systems to learn and decide with machine learning and neural networks, recognizing patterns and making predictions through three approaches—learning by example, rules, and understanding principles.

Explore the three main types of machine learning—supervised, unsupervised, and reinforcement—covering data inputs and tasks like classification, regression, clustering, dimensionality reduction, and anomaly detection.

Explore unsupervised learning through a block clustering analogy where the machine discovers patterns without labels. See a hands-on Claude demo that shows how shapes group by detected features.

Explore supervised learning by using labeled shapes to train models that classify new data, like the yellow block, based on past labels.

Explore how machines learn versus humans, examining pattern recognition, trial and error, memorization versus understanding, and the roles of supervised, unsupervised, and deep learning with real world applications.

Discover how algorithms and mathematics power AI, examining foundational principles and their role in prediction and decision making, with approachable examples like estimating weight from height.

Explore how the sequence to sequence model underpins language models and llms by predicting the next word from prior input, enabling tasks like translation and autocorrect.

Master self-attention in transformers to understand how LLMs focus on relevant words. It remembers and weighs earlier words to build accurate context and predictions.

Identify the key players shaping AI, from commercial giants to open source communities like OpenAI, Google, Anthropic, Mistral, and Meta, and compare free basic versions.

Explore LLM capabilities like natural language understanding, a vast built-in knowledge base, and reasoning to solve problems, plus style emulation and prompt testing for diverse responses.

Explore hallucinations in llms through famous quotes, highlighting how ai generated content can sound profound yet be fabricated. Reflect on reliability, critical thinking, and responsible use of advanced ai capabilities.

Learn how rephrasing prompts with llms improves clarity and accuracy, guiding AI to deeper explanations by asking the same question in a different way.

Learn when to start a new chat and how to use a prompt helper. Craft clear, concise prompts with iterative refinement and one-question clarifications.

Empower audiences with persona prompting to tailor the AI tone; craft messages for a six-year-old or a lawyer, then write a complex email advocating data-scientist consolidation into a company.

Use interactive prompting to tailor artificial intelligence responses by asking one question at a time, building a personalized 12-week workout plan after clarifying your fitness level, goals, and preferences.