Practical Introduction to Information Theory
Information Theory in this course solves complex problems in engineering and science using a probabilistic system.
4.67 (6 reviews)
83
students
5 hours
content
Feb 2025
last update
$69.99
regular price
What you will learn
Learn how to formulate problems as probability problems.
Solve probability problems using information theory.
Understand how information theory is the basis of a machine learning approach.
Learn the mathematical basis of information theory.
Identify the differences between the maximum likelihood theory approach and entropy approach
Understand the basics of the use of entropy for thermodynamics.
Calculate the molecular energy distributions using Excel.
Learn to apply Information Theory to various applications such as mineral processing, elections, games and puzzles.
Learn how Excel can be applied to Information Theory problems. This includes using Goal Seek and Excel Solver.
Understand how a Logit Transform can be applied to a probability distribution.
Apply Logit Transform to probability problems to enable Excel Solver to be successfully applied.
Solve mineral processing mass balancing problems using information theory, and compare with conventional least squares approaches.
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udemy ID
1/10/2024
course created date
2/16/2024
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