# Machine Learning Course

This course is jam-packed with everything you need to get started with machine learning. We will look at various algorithm types, such as linear regression, logistic regression, decision trees, random forest, ensembled models, and beyond. Each model type will have lectures devoted to conceptualizing its mechanics, with some easy-to-follow math as well. In addition to conceptual lectures, there will be accompanying videos on key data science theory to improve accuracy and avoid common model pitfalls. Finally, each model type will have a coding video in Python to demonstrate the algorithm in action. We will also discuss common tips and tricks for cleaning data in preparation for machine learning, as well as an overview of machine learning in R.

**Course Curriculum**

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**Module 1: **Simple Linear Regression

**Module 1:**Simple Linear Regression

******Module 2: **Multiple Linear Regression

**Module 2:**Multiple Linear Regression

******Module 3: **Logistic Regression

**Module 3:**Logistic Regression

******Module 4: **Decision Tree

**Module 4:**Decision Tree

******Module 5: **Random Tree

**Module 5:**Random Tree

******Module 6: **Model Ensembling & Unsupervised Learning

**Module 6:**Model Ensembling & Unsupervised Learning

******Module 7: **Data Cleaning

**Module 7:**Data Cleaning

******Module 8: **Additional Machine Learning in R

**Module 8:**Additional Machine Learning in R