Python Programming
Information Systems Engineering
Faculty of Technology
First Cycle (Bachelor's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Python Programming | TBL220 | Elective | Bachelor's degree | 2 | Spring | 5 |
Name of Lecturer(s)
Associate Prof. Dr. Süleyman EKEN
Assistant Prof. Dr. Seda BALTA
Learning Outcomes of the Course Unit
1) Design algorithms for engineering problems
2) Performs basic data processing practice using the calculation tool.
3) Uses advanced tools to simulate data
4) Designs computer programs using structural and object-oriented approaches.
5) Designs graphical user interface.
6) Solves basic optimization, image processing and machine learning problems in Python
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
| Learning Outcomes | ||||||||||||
| 1 | No relation | High | High | High | High | No relation | No relation | No relation | No relation | No relation | No relation | |
| 2 | No relation | High | High | High | High | No relation | No relation | No relation | No relation | No relation | No relation | |
| 3 | No relation | High | High | High | High | No relation | No relation | No relation | No relation | No relation | No relation | |
| 4 | No relation | High | High | High | High | No relation | No relation | No relation | No relation | No relation | No relation | |
| 5 | No relation | High | High | High | High | No relation | No relation | No relation | No relation | No relation | No relation | |
| 6 | No relation | High | High | High | High | No relation | No relation | No relation | No relation | No relation | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
Introduction to Programming, Introduction to Python Basic Elements of Python, Variables and Operations Control structures, Strings, Inputs, Loops Simple numerical programs Functions, Scoping and Abstraction Global Variables, Modules, Files Structural Types, Interchangeability and Higher Order Functions Arrays and Multidimensional Arrays Classes and Object Oriented Programming A Simple Introduction to Algorithmic Complexity Simple Algorithms and Data Structures. Search and Sort Algorithms Plotting Random Walks and Data Visualization Understanding Experimental Data
Weekly Schedule
1) Introduction to Programming, Introduction to Python2) Basic Elements of Python, Variables and Operations
3) Control structures, Strings, Inputs, Loops
4) Simple numerical programs
5) Functions, Scoping and Abstraction
6) Global Variables, Modules, Files
7) Structural Types, Interchangeability and Higher Order Functions
8) Midterm exam
9) Arrays and Multidimensional Arrays
10) Classes and Object Oriented Programming
11) A Simple Introduction to Algorithmic Complexity
12) Simple Algorithms and Data Structures. Search and Sort Algorithms
13) Plotting
14) Random Walks and Data Visualization
15) Understanding Experimental Data
16) Final exam
Recommended or Required Reading
1- Introduction to Computation and Programming Using Python, with Application to Understanding Data, John Guttag, Second Edition, MIT Press, 2016.
2- Python for Data Analysis, 2nd Edition Data Wrangling with Pandas, NumPy, and IPython, William McKinney, 2017
Planned Learning Activities and Teaching Methods
1) Lecture
2) Question-Answer
3) Discussion
4) Drill and Practice
5) Modelling
6) Group Study
7) Case Study
8) Lab / Workshop
9) Self Study
10) Problem Solving
11) Project Based Learning
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
50% |
|---|---|
Contribution of Final Examination to Course Grade |
50% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required