Genel Bilgi Konu Başlıkları Yeterlilik İlişkisi Değerlendirme Sistemi Öğrenme Çıktıları Özgü Ölçüt Matrisi

Hafta	Teori Konu Başlıkları
1	Introduction to Data Science: Overview, Importance, and Applications, Data Science Lifecycle
2	Data Acquisition: Sources, Methods, and Tools
3	Data Preprocessing 1: Data Cleaning, Type Conversions, Outlier Handling, and Missing Value Handling Techniques
4	Data Preprocessing 2: Normalization, Standardization, and Feature Engineering
5	Understanding Data: Data Exploration
6	Understanding Data: Data Visualization
7	Model Validation and Evaluation
8	Midterm Exam
9	Statistical Learning Models
10	Machine Learning Models
11	Resampling Methods
12	Working with Other Types of Data
13	Data Privacy, Security, and Ethics
14	Final Project Presentations and Course Review

Hafta	Uygulama Konu Başlıkları
1	Introduction to Python Programming Environment
2	Data Acquisition with Python (via web scraping, API access, CSV and Excel file reading)
3	Data Cleaning and Type Conversions
4	Data Preprocessing: Normalization and Standardization
5	Exploratory Data Analysis (EDA)
6	Data Management with SQL and Pandas
7	Data Visualization Techniques
8	Review for Midterm Exam
9	Implementing Statistical Learning Models
10	Implementing Machine Learning Models
11	Implementing Resampling Methods
12	Working with Other Types of Data
13	Business Intelligence Dashboard Creation
14	Data Privacy and Security Implementation