COURSE INFORMATION
Course Title: INFORMATION THEORY
Code Course Type Regular Semester Theory Practice Lab Credits ECTS
CEN 881 C 99 3 2 0 4 7.5
Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature) NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours: Elton Domnori
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours: NA
Teaching Assistant(s) and Office Hours: NA
Language: English
Compulsory/Elective: Elective
Classroom and Meeting Time:
Course Description: -
Course Objectives: This course covers the foundations of computer science. It will help you distinguish between what is impossible to compute and what is possible in principle to compute. It will also help you to distinguish what is feasible to compute and what is non-feasible to compute. Rigorous treatment is emphasized. Critical thinking required.
COURSE OUTLINE
Week Topics
1 What is computation? Computing models
2 Universality, Computability
3 Halting problem and non-computability
4 Kleene's Fixed point theorem
5 Class P
6 Class NP
7 Cook-Levin theorem
8 Midterm
9 Reductions and various NP complete problems
10 Savitch’s theorem
11 Approximation algorithms
12 Probabilistic algorithms
13 Cryptography
14 Review
Prerequisite(s): Basic discrete mathematics and probability.
Textbook: Introduction to the Theory of Computation, 3rd edition, Michael Sipser
Other References:
Laboratory Work: Yes
Computer Usage: Yes
Others: No
COURSE LEARNING OUTCOMES
1 Be able to distinguish between a solvable and unsolvable problem.
2 Be able to distinguish between problems that seem to have a feasible solution from those that do not.
3 How to cope with hardness of computation.
4 Foundations of cryptography
COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES
(Blank : no contribution, 1: least contribution ... 5: highest contribution)
No Program Competencies Cont.
Doctorate (PhD) in Computer Engineering Program
1 Engineering graduates with sufficient theoretical and practical background for a successful profession and with application skills of fundamental scientific knowledge in the engineering practice.
2 Engineering graduates with skills and professional background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations
3 Engineering graduates with the necessary technical, academic and practical knowledge and application confidence in the design and assessment of machines or mechanical systems or industrial processes with considerations of productivity, feasibility and environmental and social aspects.
4 Engineering graduates with the practice of selecting and using appropriate technical and engineering tools in engineering problems, and ability of effective usage of information science technologies.
5 Ability of designing and conducting experiments, conduction data acquisition and analysis and making conclusions.
6 Ability of identifying the potential resources for information or knowledge regarding a given engineering issue.
7 The abilities and performance to participate multi-disciplinary groups together with the effective oral and official communication skills and personal confidence.
8 Ability for effective oral and official communication skills in foreign language.
9 Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology.
10 Engineering graduates with well-structured responsibilities in profession and ethics.
11 Engineering graduates who are aware of the importance of safety and healthiness in the project management, workshop environment as well as related legal issues.
12 Consciousness for the results and effects of engineering solutions on the society and universe, awareness for the developmental considerations with contemporary problems of humanity.
COURSE EVALUATION METHOD
Method Quantity Percentage
Midterm Exam(s)
1
40
Quiz
2
10
Final Exam
1
40
Total Percent: 100%
ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)
Activities Quantity Duration(Hours) Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 5 80
Hours for off-the-classroom study (Pre-study, practice) 16 5 80
Mid-terms 1 12 12
Assignments 0
Final examination 1 15.5 15.5
Other 0
Total Work Load:
187.5
Total Work Load/25(h):
7.5
ECTS Credit of the Course:
7.5