11111

COURSE INTRODUCTION AND APPLICATION INFORMATION


ce.cs.ieu.edu.tr

Course Name
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
Fall
Prerequisites
 SE 116To succeed (To get a grade of at least DD)
Course Language
Course Type
Required
Course Level
-
Mode of Delivery -
Teaching Methods and Techniques of the Course Problem Solving
Application: Experiment / Laboratory / Workshop
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives
Learning Outcomes The students who succeeded in this course;
  • be able to examine the loop structures of either a recursive or nonrecursive algorithms and infer its asymptotic running time and express its efficiency using big-Oh notation
  • be able to assess the relative advantages of using array or linked list implementations in efficiently solving search problems with concurrent insertion, and/or deletions on collections of data, design
  • be able to implement efficient computer programs running at the cost of O (log n) per searching, insertion and/or deletion of data items by employing correct variants of tree data structures covered in the course
  • be able to develop efficient applications that require an order on data items by appropriately selecting the right sorting algorithm
  • be able to describe the usage of various data structures
  • be able to explain the operations for maintaining common data structures
  • be able to design and apply appropriate data structures for solving computing problems
  • be able to design simple algorithms for solving computing problems
Course Description

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction: Mathematics Review and Recursion M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 1.1, 1.2, 1.3)
2 Programming Hints M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 1.4, 1.5, 1.6, 1.7)
3 Algorithm Analysis (basic concepts of algorithms, modeling runtimes, recurrences, BigOh notations) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 2.1, 2.2, 2.3)
4 Algorithm Analysis (Running Time Calculations) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 2.4)
5 Linear Data Structures: (Pointers, Linked Lists) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 3.1, 3.2, 3.3, 3.4, 3.5)
6 Linear Data Structures (Stacks) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 3.6)
7 Linear Data Structures (Queues) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 3.7)
8 Ara sınav / Midterm
9 Trees (Binary trees) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 4.1, 4.2)
10 Trees (Binary search trees) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 4.3)
11 Trees (AVL Trees) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 4.4)
12 Priority Queues: Binary Heaps M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 6.1, 6.2, 6.3)
13 Sorting (Insertion Sort, Shellsort) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 7.1, 7.2, 7.3, 7.4)
14 Sorting (Heapsort, Mergesort ) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 7.5, 7.6)
15 Sorting (Quicksort) M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006 (Ch. 7.7)
16 Review of the Semester  
Course Notes/Textbooks M. A. Weiss, Data Structures and Algorithm Analysis in C++, 3/e, AddisonWesley, 2006
Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
10
30
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
60
Weighting of End-of-Semester Activities on the Final Grade
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
2
Study Hours Out of Class
15
3
Field Work
Quizzes / Studio Critiques
5
2
Portfolio
Homework / Assignments
2
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
1
15
Final Exams
1
20
    Total
170

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

Adequate knowledge in Mathematics, Science and Computer Engineering; ability to use theoretical and applied information in these areas to model and solve Computer Engineering problems

X
2

Ability to identify, define, formulate, and solve complex Computer Engineering problems; ability to select and apply proper analysis and modeling methods for this purpose

X
3

Ability to design a complex computer based system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose

X
4

Ability to devise, select, and use modern techniques and tools needed for Computer Engineering practice

X
5

Ability to design and conduct experiments, gather data, analyze and interpret results for investigating Computer Engineering problems

X
6

Ability to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; ability to work individually

7

Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of two foreign languages

8

Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself

9

Awareness of professional and ethical responsibility

10

Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development

X
11

Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Computer Engineering solutions

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 

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