Lecture 1: Data Types: Numerical, Categorical and Ordinal

Lecture 2: Mean, Median and Mode

Lecture 3: Normal Data Distribution

Lecture 4: Variance and Standard Deviation

Lecture 5: Covariance and Correlation

Lecture 1: File Reading and Writing

Lecture 2: Database Connection with Pandas

Lecture 3: Data Filtering and Aggregation

Lecture 4: Pivot Tables and Conditional Assignment

Lecture 1: Linear Regression

Lecture 2: Logistic Regression

Lecture 3: K-Means Clustering

Lecture 4: K-Nearest Neighbors (KNN)

Lecture 5: Decision Trees

Lecture 6: Random Forest

Lecture 7: XGBoost