Information Package / Course Catalogue
Data Science and Machine Learning With Python
Course Code: UTFY520
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

The course aims to provide students with an introduction to data science and machine learning using the Python programming language. Students will learn basic Python commands and topics that provide an introduction to data science and machine learning using the Python programming language. The course will help students understand the use of basic Python commands and how they apply them to data science and machine learning. Fundamental concepts of data science and the working principles of machine learning algorithms will be introduced. Additionally, students will learn how to use Python to extract summary statistics from data sets, summarize and visualize data, organize data sets and test their reliability, develop machine learning models, and

Course Content

The "Data Science and Machine Learning with Python" course is designed to cover the fundamentals of data science and machine learning. Students will receive comprehensive training in the Python programming language, which can be used in data science, machine learning, and deep learning. The course will cover fundamental concepts of the Python programming language and the use of specialized libraries in Python for data science and machine learning. The course will cover topics such as data visualization, data exploration, feature selection, predictive models, and model performance evaluation using Python. Information about Python libraries used in deep learning and machine learning is also provided.

Name of Lecturer(s)
Assoc. Prof. Sadullah ÇELİK
Learning Outcomes
1.Students will learn the necessary coding to develop data science and machine learning models with the help of Python language.
2.Students will be able to identify and solve data science and machine learning problems.
3.Students will learn to measure the performance of data science and machine learning models with the help of Python language.
4.Students will learn how to make the output of data science and machine learning models understandable and comprehensible with the help of the Python language.
5.Students will learn the necessary preprocessing and feature clustering techniques to improve the predictive performance of data science and machine learning models with the help of Python language.
Recommended or Required Reading
1.Ramalho, L. (2022). Fluent python. " O'Reilly Media, Inc."
2.Haslwanter, T. (2016). An Introduction to Statistics with Python. With Applications in the Life Sciences.. Switzerland: Springer International Publishing.
Weekly Detailed Course Contents
Week 1 - Theoretical
Overview of Data Science and Machine Learning. Python fundamentals.
Week 2 - Theoretical
Fundamental Data Classes and Operators.
Week 3 - Theoretical
Data Structures and Programming Control Structures
Week 4 - Theoretical
Data Visualization: Matplotlib, Seaborn, ggplot.
Week 5 - Theoretical
Data preprocessing: Pandas, Numpy, Scikit-Learn.
Week 6 - Theoretical
Linear Regression.
Week 7 - Theoretical
K-Nearest Neighbor Algorithm
Week 8 - Theoretical
K-Means Algorithm
Week 9 - Theoretical
Decision trees and Random Forests
Week 10 - Theoretical
Artificial Neural Networks.
Week 11 - Theoretical
Deep Learning
Week 12 - Theoretical
Applications of Machine Learning
Week 13 - Theoretical
Advanced Applications of Machine Learning.
Week 14 - Theoretical
Data Science and Machine Learning Projects.
Week 15 - Theoretical
Project Presentation and Evaluation
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory153390
Assignment2228
Reading33215
Midterm Examination1156
Final Examination1156
TOTAL WORKLOAD (hours)125
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
OÇ-1
2
2
4
2
3
OÇ-2
2
2
4
3
2
OÇ-3
3
2
3
2
2
OÇ-4
3
2
4
2
3
OÇ-5
2
2
2
3
2
Adnan Menderes University - Information Package / Course Catalogue
2026