Lecture 1: Covariance and Correlation

Lecture 2: Mean, Median and Mode

Lecture 3: Normal Data Distribution

Lecture 4: Data Types: Numerical, Categorical and Ordinal

Lecture 5: Variance and Standard Deviation

Lecture 1: Database Connection with Pandas

Lecture 2: Data Filtering and Aggregation

Lecture 3: File Reading and Writing

Lecture 4: Pivot Tables and Conditional Assignment

Lecture 1: Decision Trees

Lecture 2: K-Means Clustering

Lecture 3: K-Nearest Neighbors (KNN)

Lecture 4: Linear Regression

Lecture 5: Logistic Regression

Lecture 6: Random Forest

Lecture 7: XGBoost