ected and elegant ways. It is at the very interface of these two fields and cultures, classical and quantum information theory, that this textbook takes a crucial place and also innovates in the descriptive approach. I have spent SO much time as Head of the Physics Department in my University convincing students and researchers to kick against the partitioning between physics and science in general, that I am very pleased to welcome this work Emmanuel Desurvire, which is a model of scientific "hybridization." Combining the cultures of a physicist (as a researcher), an academic (as a former professor and author of several books), and an engineer (as a developer and project manager) from the telecom industry, Emmanuel Desurvire attempts here to bridge the gap between the CIT and QIT cultures. On the CIT side, fundamentals, such as information, entropy, mutual entropy, and Shannon capacity theorems, are reviewed in detail, using a wealth of practical and original application examples. Worth mentioning are the reputedly difficult notions of Kolmogorov complexity and Turing machines, which were developed independently from Shannon during the same historical times, described herewith with thrust and clarity, again with original examples and illustrations. The mind-boggling (and little-known) conclusion to be retained is that Kolmogorov complexity and Shannon entropy asymptotically converge towards each other, despite fundamentally different ground assumptions. Then, under any expectation for a textbook in this subject, comes a detailed (and here quite vivid) description of various principles of data compression (coding optimality, integer, arithmetic, and adaptive compression) and error-correction coding (block and cyclic codes). Shannon's classical theory of information then moves on and concludes with the channel-capacity theorems, including the most elegant Shannon- Hartley theorem of incredibly simple and universal formulation, C = log(1 + SNR), Foreword which relates the channel capacity (C) to the signal-to-noise