The mathematics of communication — Shannon's 1948 foundation through modern capacity-approaching codes. Bits, surprise & self-information, entropy and its joint, conditional, cross & relative (KL) flavors, mutual information, source coding (Huffman, arithmetic, Lempel-Ziv, DEFLATE, BWT, Brotli, Zstandard), lossy & perceptual coding (JPEG, MP3, AAC, Opus, H.264, AV1), Kolmogorov complexity, noisy channels & the Shannon-Hartley capacity theorem, error detection (parity, checksums, CRC) & correction (Hamming, Reed-Solomon, BCH, Golay, convolutional + Viterbi, turbo, LDPC, polar), rate-distortion theory, quantum information (qubits, no-cloning, Holevo bound), and real-world applications from Voyager to 5G to deep learning's cross-entropy loss. 30 units · 450 lessons.