
| 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 |
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
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.
| Assoc. Prof. Sadullah ÇELİK |
| 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. |
| 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. |
| Type of Assessment | Count | Percent |
|---|---|---|
| Midterm Examination | 1 | %30 |
| Final Examination | 1 | %70 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 15 | 3 | 3 | 90 |
| Assignment | 2 | 2 | 2 | 8 |
| Reading | 3 | 3 | 2 | 15 |
| Midterm Examination | 1 | 1 | 5 | 6 |
| Final Examination | 1 | 1 | 5 | 6 |
| TOTAL WORKLOAD (hours) | 125 | |||
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 |