◾ Data Exploration and Cleaning
◾ Dealing with Missing Values
◾ Data Formatting in Python
◾ Data Normalization in Python
◾ Turning Categorical into Quantitative variables
◾ Activity-2: Data Cleaning and Exploring Data

◾ Introduction to Machine Learning
◾ Supervised and Unsupervised
◾ Python for Machine Learning
◾ Model Performance Metrics
◾ Activity 3: Performing Basic Machine Learning Algorithm using Python

◾ Introduction to Regression
◾ Plotting Regression
◾ Simple and Multiple Linear Regression
◾ Overfitting and Underfitting
◾ Polynomial Regression
◾ Activity 4: Implementing a Regression Model

◾ Introduction to Classification
◾ K-Nearest Neighbours
◾ Evaluation Metrics
◾ Logistic Regression
◾ Logistic vs Linear Regression
◾ Decision Trees
◾ Activity 5: Implementing a Classification Model

◾ Introduction to Clustering
◾ K-Means Clustering
◾ DBSCAN and Hierarchical Clustering
◾ Activity 6: Implementing a Clustering Model