Akademik Dersler - İçerik

Weeks	Topics
Week - 1	Introduction to the course and feature engineering.
Week - 2	Handling missing values and imputation techniques are introduced.
Week - 3	Different encoding methods for categorical variables are covered.
Week - 4	Scaling and normalization of numerical data are applied.
Week - 5	Data transformations and interaction-based feature creation are practiced.
Week - 6	Feature extraction from temporal and time-series data is performed.
Week - 7	Numerical features are extracted from text data.
Week - 8	Basic feature selection methods are introduced.
Week - 9	Advanced feature selection methods are applied.
Week - 10	Dimensionality reduction techniques such as PCA are explained.
Week - 11	Visualization and dimensionality reduction with t-SNE and UMAP are performed.
Week - 12	Automated feature engineering tools are introduced.
Week - 13	A hands-on project is conducted on large datasets.
Week - 14	Project presentations and overall evaluation are carried out.