and contain other compartments such as mitochondria. Living things also share a set of properties: they use energy, grow, respond to their surroundings, keep their internal conditions stable, reproduce, and evolve over generations. Keep that list handy; it is how biologists decide what counts as alive." }, { "id": "astro101", "title": "Astronomy: Stars, Planets and the Cosmos", "host": "grok", "desc": "A tour of the night sky: light, telescopes, the solar system, the life of stars and the expanding universe.", "lessons": ["Reading the night sky", "Light and telescopes", "The solar system", "How stars are born and die", "Galaxies and the expanding universe"], "intro": "Astronomy is the oldest science, and it starts with simply looking up. The sky appears to turn once a day because Earth rotates on its axis, so stars rise in the east and set in the west, while the star Polaris stays almost fixed above the north pole. Astronomers divide the sky into 88 official constellations, like Orion and Scorpius, which are patterns seen from Earth rather than physical groups. Distances are huge: light from the Sun takes about eight minutes to reach us, and from the nearest other star, Proxima Centauri, about 4.2 years, which is why we say it is 4.2 light-years away. Every time you look at a star, you are looking back in time." } ] }, { "id": "mathcs", "name": "Mathematics & Computer Science / AI", "host": "playa2", "blurb": "The language of patterns and the science of computation, from proofs and algorithms to machine learning.", "courses": [ { "id": "math101", "title": "Calculus I: Limits and Derivatives", "host": "playa2", "desc": "Rates of change and the derivative, built carefully from limits, with applications to motion and optimisation.", "lessons": ["Functions and their graphs", "Limits and continuity", "The derivative as a rate of change", "Rules of differentiation", "Applications: motion and optimisation"], "intro": "A function is a rule that assigns exactly one output to each input: f(x) = x squared sends 3 to 9 and minus 3 to 9 as well. We study functions through their graphs, the set of points (x, f(x)), and through key features such as where they increase or decrease, where they cross the axes, and how they behave for very large inputs. Calculus asks a deeper question: how fast is the output changing at a single instant? To answer it we will need limits, the value a function approaches as the input gets close to a point. Before that, make sure you can read a graph fluently, because every idea in this course can be drawn." }, { "id": "cs101", "title": "Introduction to Programming", "host": "playa2", "desc": "Think like a programmer: variables, control flow, functions and data structures, using clear, testable code.", "lessons": ["Algorithms and programs", "Variables, types and expressions", "Conditions and loops", "Functions and decomposition", "Lists, maps and data structures", "Testing and debugging"], "intro": "An algorithm is a finite, precise sequence of steps that solves a problem, like a recipe that a machine can follow without guessing. A program is an algorithm written in a programming language such as Python or JavaScript so a computer can execute it. Good algorithms are correct, meaning they give the right answer for every valid input, and efficient, meaning they do not waste time or memory. Programmers break big problems into small steps, name those steps clearly, and test each one. In this course you will learn to read a problem, sketch an algorithm in plain words, and only then turn it into code; that habit matters more than any single language." }, { "id": "ai101", "title": "Foundations of Artificial Intelligence", "host": "playa2", "desc": "What AI is and is not: search, probability, machine learning, neural networks and language models, plus their limits and ethics.", "lessons": ["What is artificial intelligence?", "Search and problem solving", "Probability and learning from data", "Neural networks", "Large language models", "AI safety and ethics"], "intro": "Artificial intelligence is the field of building systems that perform tasks we associate with intelligence, such as recognising images, planning, translating or answering questions. Early AI, from the 1950s on, relied mostly on hand-written rules and search: the program explored possible moves or steps and picked the best by a scoring rule, which is how classic chess engines worked. Modern AI is dominated by machine learning, where a system learns patterns from examples instead of being told the rules. Large language models, for instance, are neural networks trained on huge amounts of text to predict the next token. They can be remarkably capable, yet they can also be confidently wrong, which is why understanding how they wo