Information Theory

Code:

CC4019

Acronym:

CC4019

Level:

400

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2018/2019 - 1S

Active?	Yes
Responsible unit:	Department of Computer Science
Course/CS Responsible:	Master in Computer Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:CC	2	Study plan since 2014/2015	1	-	6	42	162
M:ENM	0	Official Study Plan since 2013-2014	1	-	6	42	162
			2
MI:ERS	25	Plano Oficial desde ano letivo 2014	4	-	6	42	162
M:M	0	Plano de Estudos do M:Matemática	1	-	6	42	162
			2

Teaching language

Portuguese

Objectives

The aim of of information theory is to expose fundamental concepts related to information and its applications in systems and communications networks and computer science.

Learning outcomes and competences

At the end of the course, students are expected to: have understood how the quantity of information can be measure; understood the concept and properties of entropy and mutual information as applied to information; have understood, and be able to prove, the noiseless coding theorem (Shannon's First Theorem); have understood the notions of channels, different classes of channels, and channel capacity, have understood the fundamental coding theorem for noisy channels (Shannon's Second Theorem), and its implications; have understood simple methods for construction of error correcting codes; have understood the theory of rate-distortion.

Working method

Presencial

Program

At the end of the course, students are expected to: have understood how the quantity of information can be measure; understood the concept and properties of entropy and mutual information as applied to information; have understood, and be able to prove, the noiseless coding theorem (Shannon's First Theorem); have understood the notions of channels, different classes of channels, and channel capacity, have understood the fundamental coding theorem for noisy channels (Shannon's Second Theorem), and its implications; have understood simple methods for construction of error correcting codes; have understood the theory of rate-distortion. Algorithmic information theory.

Mandatory literature

000089002. ISBN: 978-0-471-24195-9

Teaching methods and learning activities

The discipline of Information Theory includes about 30 hours of exposure for theoretical teaching and 15 hours of exercises.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Teste	100,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	130,00
Frequência das aulas	34,50
Total:	164,50

Eligibility for exams

It is mandatory to have an average of 8 out of 20 in the two tests to be able to do the final exam.

Calculation formula of final grade

Distributed evaluation with final exam: students are assessed by their performance with  two tests.  It is mandatory to have an average of 8 out of 20 in the two tests to be able to do the final exam. If the student has an average bigger than 10 out of 20 in the tests he will allowed to keep the grade without the final exam, otherwise the final classification will be the average of the final exam with the average of the tests.