Introduction to Information Measurement and Theory
Learn how digital information is quantified, measured, and calculated using core theoretical and probabilistic approaches.
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AI instructor
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Start anytime
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In English
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About this course
Information is a fundamental quantity that powers our modern digital world, yet measuring it requires clear concepts and mathematical framework. This text-based course guides you through the foundational principles of information theory, enabling you to analyze data volume, uncertainty, and message content. What you'll learn: Understand fundamental units of digital information including bits, bytes, and their higher orders. Explore both alphabetical and probabilistic approaches to measuring information quantity. Calculate information content using core mathematical models such as Hartley's and Shannon's formulas. Examine data compression concepts, message redundancy, and encoding efficiency. Connect theoretical concepts to modern digital storage and communication systems. The course begins with essential terminology, basic definitions, and core principles before guiding you through structured written examples and exercises. Designed for beginners in computer science or data fundamentals, with no advanced prerequisites required. Start reading today to build a solid foundation in quantifying digital information.
What you'll get
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Certificate of completion
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Personal AI tutor
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Lifetime access
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Phone or computer
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14-day refund
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Short & focused
2h 54m of practical content
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Frequently asked
What do I need to take this course? +
Just a phone or computer with internet. No installs, no special hardware.
How do I pay? +
By card via Stripe. We donโt store card details โ Stripe handles them securely.
Can I get a refund? +
Yes โ full refund within 14 days, no questions asked.
How long will I have access? +
Forever. Once you purchase, the course is yours to revisit anytime.
Will I get a certificate? +
Yes. On completion you'll receive a certificate you can add to your LinkedIn profile.
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