Artificial Intelligence - Easily Explained For Beginners

This video course on artificial intelligence is aimed at beginners and is designed to teach you the basics within the historical development of AI. For this reason, our journey begins with the section "Introduction and historical background of AI". Topics and contents of the lessons:I.

Introduction and historical backgroundWhat is AI - a philosophical considerationStrong and Weak AIThe Turing TestThe birth of the AIThe era of great expectationsCatching up with realityHow to teach a machine to learnDistributed systems in the AIDeep Learning, Machine Learning, Natural Language ProcessingII. The general problem solverProof Program - Logical TheoristExample from "Human Problem Solving" (Simon)The structure of a problemIn this section, we first take up the initial techniques of AI. You will learn about the concepts and famous example systems that triggered this early phase of euphoria.

III. Expert SystemsFactual knowledge and heuristic knowledgeFrames, Slots and FillerForward and backward chainingThe MYCIN ProgrammeProbabilities in expert systemsExample - Probability of hairline cracksIn this section, we discuss expert systems that, similar to the general problem solvers, only deal with specific problems. But instead, they use excessive rules and facts in the form of a knowledge base.

IV. Neuronal NetworksThe human neuronSignal processing of a neuronThe PerceptronThis section heralds a return to the idea of being able to reproduce the human brain and thus make it accessible to digital information processing in the form of neural networks. We look at the early approaches and highlight the ideas that were still missing to help neural networks achieve a breakthrough.