At the end of this course, the students; 1) Can develop algorithms for problem solving. 2) Develop understaning about computer programming languages. 3) Can discuss about modular programming and functions. 4) Can do programming. 5) Can define simple computer programs.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
In this course, the fundamentals of computer programming will be discussed and various programming environments will be introduced to the students. The course will involve topics such as general programming, algorithms and debugging, data types, sets and strings, comparison operators and iterations, functions, different programming languages and their properties, and Psychophysics Toolbox. Supported by projects, this course will also cover the usage of computer programming in experimental design and data analysis, the application of simple statistical principles and graph plotting.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Introduction to Programming
2nd Week
Algorithm Development I
3rd Week
Algorithm Development II
4th Week
Algorithm Development III
5th Week
Introduction to Python Programming Language I
6th Week
Introduction to Python Programming Language II
7th Week
Introduction to Python Programming Language III
8th Week
Introduction to Python Programming Language IV
9th Week
Commands and directories
10th Week
Series
11th Week
Programming Functions
12th Week
Advanced Programming I
13th Week
Advanced Programming II
14th Week
Advanced Programming III
RECOMENDED OR REQUIRED READING
Aziz, A., Lee, T-H & Prakash, A. (2016). Elements of programming interviews in Python: The insiders? guide. South Carolina: CreateSpace IPP. * The basic materials to be used in this course are updated every year.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Discussion,Other
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Project
1
60
Total(%)
60
Contribution of In-term Studies to Overall Grade(%)
60
Contribution of Final Examination to Overall Grade(%)
40
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
Preparation for Quiz
Individual or group work
14
5
70
Preparation for Final exam
1
24
24
Course hours
14
3
42
Preparation for Midterm exam
Laboratory (including preparation)
Final exam
1
3
3
Homework
1
160
160
Total Workload
299
Total Workload / 30
9,96
ECTS Credits of the Course
10
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
