ECTS - Discrete Computational Structures

Discrete Computational Structures (CMPE251) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Discrete Computational Structures CMPE251 3 0 0 3 7
Pre-requisite Course(s)
N/A
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Discussion, Question and Answer.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The objective of this course is to teach mathematical concepts that are fundamental to computer science.
Course Learning Outcomes The students who succeeded in this course;
  • Apply mathematical reasoning and combinatorial analysis
  • Design discrete structures for computations
  • Apply algorithmic thinking
  • Formulate problems using mathematical structure
Course Content Basic mathematical objects of computational mathematics: sets, sequences, relations, functions, and partitions; deductive mathematical logic proof techniques; discrete number systems; induction and recursion; graphs and sub-graphs; trees; planarity of graphs; covering problems; path problems; directed graphs; combinatorics.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 The Foundations: Logic, Sets and Functions Chapter 1.1, 1.2, 1.3 (main text)
2 The Foundations: Logic, Sets and Functions Chapter 1.4, 1.5, 1.6.
3 The Foundations: Logic, Sets and Functions Chapter 2.1, 2.2, 2.3, 2.4.
4 The Fundamentals: Algorithms, the Integers and Matrices Chapter 3.1, 3.2, 3.3.
5 The Fundamentals: Algorithms, the Integers and Matrices Chapter 3.4, 3.5
6 The Fundamentals: Algorithms, the Integers and Matrices Chapter 3.6, 3.8.
7 Mathematical Reasoning Chapter 4.1.
8 Mathematical Reasoning Chapter 4.3.
9 Counting Chapter 5.1, 5.2.
10 Counting Chapter 5.3
11 Relations Chapter 8.1, 8.3.
12 Graphs Chapter 9.1, 9.2.
13 Graphs Chapter 9.3, 9.4, 9.5.
14 Trees Chapter 10.1
15 Review
16 Review

Sources

Course Book 1. Discrete Mathematics and Its Applications, K.H. Rosen, 7th. Edition, McGraw-Hill, 2011.
Other Sources 2. Discrete Mathematics, K.A. Ross, C.R.B. Wright, Fourth Edition, Prentice Hall, 1999.
4. Discrete and Combinatorial Mathematics, An Applied Introduction, R.P. Grimaldi, Fifth Edition, Addison Wesley, 2003.
5. Discrete Mathematics, R. Johnsonbaugh, Seventh Edition, Prentice Hall, 2008
6. Discrete Mathematics with Applications, S.S.Epp, First Edition, Thomson, 2003.
7. Discrete Mathematics with Combinatorics, J.A.Anderson, Second Edition, Prentice Hall, 2003.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation 1 10
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 55
Final Exam/Final Jury 1 35
Toplam 4 100
Percentage of Semester Work 65
Percentage of Final Work 35
Total 100

Course Category

Core Courses
Major Area Courses
Supportive Courses X
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge in mathematics, science and computing fields; ability to apply theoretical and practical knowledge of these fields in solving engineering problems related to information systems. X
2 Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. X
3 Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose.
4 Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in information systems engineering applications; ability to use information technologies effectively.
5 Ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the information systems discipline. X
6 Ability to work effectively in inter/inner disciplinary teams; ability to work individually.
7 a. Effective oral and written communication skills in Turkish; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. b. Knowledge of at least one foreign language; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8 Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development.
9 a. Ability to behave according to ethical principles, awareness of professional and ethical responsibility. b. Knowledge of the standards utilized in information systems engineering applications.
10 a. Knowledge on business practices such as project management, risk management and change management. b. Awareness about entrepreneurship, and innovation. c. Knowledge on sustainable development.
11 a. Knowledge of the effects of information systems engineering applications on the universal and social dimensions of health, environment, and safety. b. Awareness of the legal consequences of engineering solutions.
12 An ability to design, develop, operate and manage cost-effective information systems by assembling the most appropriate software and hardware, arranging appropriate personnel, and defining necessary procedures, in order to enable public and private sector organizations to do their jobs more effectively and be more competitive. X
13 Skills in finding solutions to business problems using information technologies.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 4 64
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 15 30
Prepration of Final Exams/Final Jury 1 30 30
Total Workload 172