Course Weekly Lecture Plan

Week	Topic
1	Introduction to Machine Learning with Python Preparing the Environment for Machine Learning
2	Python Libraries for Machine Learning, Data Visualization
3	Supervised Learning (K-Nearest Neighbors)
4	Supervised Learning (Decision Trees, Random Forest)
5	Supervised Learning (Naive Bayes Classifiers)
6	Supervised Learning (Linear Regression, Logistic Regression)
7	Unsupervised Learning (k-Means Clustering)
8	Unsupervised Learning (Hierarchical Clustering)
9	Unsupervised Learning (Density Based Clustering)
10	Unsupervised Learning (Mixture Models)
11	Project Presentations