Information Theory

Measuring information in bits. Entropy, mutual information, source coding and Huffman codes, channel models and the Shannon capacity limit that governs every compression scheme and communication link.

• Entropy, Information & Coding — Information theory measures information in bits. Learn self-information, Shannon entropy, joint and conditional entropy, mutual information, the source-coding theorem, Huffman coding, the binary symmetric channel and how these ideas set the limits of compression and communication — with Python entropy calculations.
• Shannon Channel Capacity — Information theory sets the ultimate limits. Learn information and entropy, source coding (Huffman), channel capacity C = B log₂(1 + SNR), the Shannon limit Eb/N₀ ≥ −1.6 dB, bandwidth vs power trade-offs, and how modern codes approach capacity.