Principles of Information Engineering

This course presents the principles and techniques fundamental to the representation, processing and transmission of information. It equips students with the knowledge and tools to answers questions such as: What is information and how to quantify it? How much can we compress data without distortion? How to reliably store and transmit information in a way that is robust to data corruption? And how to learn from data with uncertainty? The answers to these questions often find their applications in electronic and computer engineering fields and beyond, such as electronic systems, control systems, telecommunication systems, computer systems, machine learning, data science, neuroscience, bioinformatics and linguistics. The course begins by introducing the basic concepts of probability and random variables, leading to probabilistic inference. It then continues with the following topics: concepts and tools of information theory, data compression principles and algorithms, error detection and correction codes for data storage and transmission, digital modulation and communication channel characteristics.