Foundational Information Theory and Data Transmission

Do you want to understand the fundamental laws that govern all digital communication, data storage, and computation? Information Theory provides the mathematical framework for measuring and transmitting data efficiently and reliably. This course grounds you in the principles of Systems Theory and Information Theory, enabling you to analyze, quantify, and model the flow of information. You will gain a deep appreciation for concepts like entropy, redundancy, and channel limits that define modern technology. What you'll learn: * Understand the core definitions and objectives of Systems Theory and how to classify different types of Information Systems. * Learn the mathematical models for quantifying information using Shannon Entropy and calculating information redundancy. * Analyze the characteristics of data transmission channels, including signal types, noise, and maximum channel capacity. * Apply theoretical limits to real-world scenarios, such as assessing data compression efficiency and error detection capability. * Practice configuring basic mathematical models of signal transmission and understanding their role in communication engineering. We begin with foundational systems concepts before diving into Information Theory. The course progresses through mathematical definitions of information and entropy, culminating in the study of signal modeling and the limits of data transmission channels. This course is designed for absolute beginners in computer science, engineering, or mathematics who seek a rigorous theoretical foundation. No prior knowledge of information theory or advanced mathematics is required. Start building your expertise in the fundamental science of information today.