Information Theory Course
This course equips you with hands-on skills in information theory for real-world applications. Learn to model data sources like English text logs, compute entropy and compression ratios, design optimal Huffman codes, analyse noisy channels for error rates, and balance compression efficiency with reliability to enhance performance in data systems and modern tech.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain practical mastery in information theory, covering entropy calculations, fixed-length and prefix-free coding, Huffman-style designs, modelling symbol sources, compression efficiency, noisy channel analysis, error detection, correction, and trade-offs for building reliable, efficient data systems.
Elevify advantages
Develop skills
- Design entropy-based codes by computing H, bits per symbol, and inefficiency quickly.
- Build Huffman-style prefix codes to map symbols to optimal bitstrings efficiently.
- Model text sources and estimate symbol probabilities from real English logs.
- Analyse noisy channels to quantify bit errors, propagation, and bit error rates.
- Balance compression and reliability by selecting block sizes, redundancy, and testing methods.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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