You must be logged in to take this course → LOGIN | REGISTER NOW

Information theory is the mathematical theory that deals with the fundamental aspects of communication systems. This **[course_title]** is meant to serve as an introduction to some basic concepts in information theory and error-correcting codes, and some of their applications in computer science and statistics. It covers the basics of information theory like the information associated with an event, entropy, mutual information, data processing theorem, source coding, Huffman codes, channel capacity and the channel coding theorem.

**Assessment**

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

**Certification**

Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

- Add the certificate to your CV or resume and brighten up your career
- Show it to prove your success

Course Credit: Open Culture

### Course Curriculum

module :1 | |||

Mod-01 Lec-01 Introduction to Information Theory and Coding | 00:53:00 | ||

Mod01 Lec-02 Definition of Information Measure and Entropy | 00:53:00 | ||

Mod-01 Lec-03 Extension of An Information Source and Markov Source | 00:56:00 | ||

Mod-01 Lec-04 Adjoint of An Information Source, Joint and Conditional Information Measures | 00:57:00 | ||

Mod-01 Lec-05 Properties of Joint and Conditional Information Measures and a Markov Source | 00:50:00 | ||

Mod-01 Lec-06 Asymptotic Properties of Entropy and Problem Solving in Entropy | 00:56:00 | ||

Mod-01 Lec-07 Block Code and Its Properties | 00:51:00 | ||

Mod-01 Lec-08 Instantaneous Code and Its Properties | 00:52:00 | ||

Mod-01 Lec-09 Kraft-Mcmillan Equality and Compact Codes | 00:52:00 | ||

Mod-01 Lec-10 Shannon`s First Theorem | 00:52:00 | ||

module : 2 | |||

Mod-01 Lec-11 Coding Strategies and Introduction to Huffman Coding | 00:54:00 | ||

Mod-01 Lec-12 Huffman Coding and Proof of Its Optimality | 00:54:00 | ||

Mod-01 Lec-13 Competitive Optimality of The Shannon Code | 00:51:00 | ||

Mod-01 Lec-14 Non-Binary Huffman Code and Other Codes | 00:48:00 | ||

Mod-01 Lec-15 Adaptive Huffman Coding part-1 | 00:51:00 | ||

Mod-01 lec-16 Adaptive Huffman Coding Part-2 | 00:49:00 | ||

Mod-01 Lec-17 Shannon-Fano-Elias Coding and Introduction to Arithmetic Coding | 00:53:00 | ||

Mod-01 Lec-18 Arithmetic Coding Part-1 | 00:50:00 | ||

Mod-01 Lec-19 Arithmetic Coding Part-2 | 00:52:00 | ||

Mod-01 Lec-20 Introduction to Information Channel | 00:56:00 | ||

module : 3 | |||

Mod-01 Lec-21 Equivocation and Mutual Information | 00:52:00 | ||

Mod-01 Lec22 Properties of Different Information Channels | 00:54:00 | ||

Mod-01 Lec-23 Reduction of Information Channels | 00:51:00 | ||

Mod-01 Lec-24 Properties of Mutual Information and Introduction to Channel Capacity | 00:52:00 | ||

Mod-01 Lec-25 Calculation of Channel Capacity for Different Information Channel | 00:47:00 | ||

Mod-01 Lec-26 Shannon`s Second Theorem | 00:50:00 | ||

Mod-01 Lec-27 Discussion on Error Free Communication Over Noisy Channel | 00:53:00 | ||

Mod-01 Lec-28 Error Free Communication Over a Binary Symmetric Channel | 00:50:00 | ||

Mod-01 Lec-29 Differential Entropy and Evaluation of Mutual Information | 00:16:00 | ||

Mod-01 Lec-30 Channel Capacity of a Bandlimited Continuous Channel | 00:56:00 | ||

module : 4 | |||

Mod-01 Lec-31 Introduction to Rate-Distortion Theory | 00:49:00 | ||

Mod-01 Lec-32 Definition and Properties of Rate-Distortion Functions | 00:47:00 | ||

Mod-01 Lec-33 Calculation of Rate-Distortion Functions | 00:54:00 | ||

Mod-01 Lec-34 Computational Approach For Calculation of Rate-Distortion Functions | 00:49:00 | ||

Mod-01 Lec-35 Introduction to Quantization | 00:51:00 | ||

Mod-01 Lec-36 Lloyd-Max Quantizer | 00:49:00 | ||

Mod-01 Lec-37 Companded Quantization | 00:58:00 | ||

Mod-01 Lec-38 Variable Length Coding and Problem Solving In Quantizer Design | 00:51:00 | ||

Mod-01 Lec-39 Vector Quantization | 00:55:00 | ||

Mod01 Lec-40 Transform Part-1 | 00:52:00 | ||

Mod-01 Lec-41 Transform Coding Part-2 | 00:54:00 | ||

Assessment | |||

Submit Your Assignment | 00:00:00 | ||

Certification | 00:00:00 |

### Course Reviews

No Reviews found for this course.

**8 STUDENTS ENROLLED**