COURSE UNIT TITLE

: COMPUTER PROGRAMMING I

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BIL 2205 COMPUTER PROGRAMMING I COMPULSORY 2 2 0 6

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ENGIN YILDIZTEPE

Offered to

Statistics
Statistics(Evening)

Course Objective

This course aims to equip students with algorithmic thinking, computer-oriented problem-solving, and coding skills using a modern programming language.

Learning Outcomes of the Course Unit

1   Design algorithms and express them using pseudocode and flowcharts.
2   Write computer program for an algorithm.
3   Use control structures.
4   Define functions.
5   Use modules and built-in functions.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Computer, programming concepts, algorithm definition, and introduction to Python.
2 Python syntax, variables, data types, basic input/output operations.
3 Number systems, Operators, and numerical operations in Python.
4 Expressing algorithms: pseudocode, flowcharts.
5 Simple algorithms and Python applications.
6 Control structures, conditional statements.
7 Loop concepts and repetitive operations.
8 Loops, Nested loops.
9 Lists and string operations, sorting and searching.
10 Functions, basic mathematical and statistical functions.
11 Python modules: Numpy.
12 Python modules: Pandas and Matplotlib.
13 Using Large Language Models (LLMs) for coding and debugging assistance.
14 General review, problem-solving, mini project presentations.

Recomended or Required Reading

Ana Kaynak: Think Python, 3rd edition, Allen B. Downey, 2024.
Yardımcı kaynaklar:
1 - CS for All: An Introduction to Computer Science Using Python, Christine Alvarado, Zachary Dodds, Geoff Kuenning, Ran Libeskind-Hadas, 2019.
2 - Introduction to Computation and Programming Using Python, 3rd Edition, John V. Guttag, MIT Press, 2021.

Planned Learning Activities and Teaching Methods

Lecture, presentation, computer exercises, and problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 VZ Vize
2 FN Final
3 BNS BNS VZ * 0.40 + FN * 0.60
4 BUT Bütünleme Notu
5 BBN Bütünleme Sonu Başarı Notu VZ * 0.40 + BUT * 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams.

Language of Instruction

English

Course Policies and Rules

Students are required to attend classes in accordance with the faculty's teaching and examination regulations throughout the semester. Students must adhere to class schedules and assignment deadlines. Any unethical behavior that may occur in classes and exams will be evaluated according to the relevant regulations. You can obtain the D.E.Ü. Faculty of Science teaching and exam application regulations from https://fen.deu.edu.tr/.

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-posta: engin.yildiztepe@deu.edu.tr
Tel: 0232 301 86 04

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Tutorials 14 2 28
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 20 20
Preparation for final exam 1 25 25
Preparing assignments 2 15 30
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 149

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.155
LO.255
LO.355
LO.455
LO.555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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