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Machine Learning with Python Training

Machine Learning with Python

This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.
Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!

Explore many algorithms and models:

  • Popular algorithms: Classification, Regression, Clustering, and Dimensional Reduction.
  • Popular models: Train/Test Split, Root Mean Squared Error, and Random Forests.

Get ready to do more learning than your machine!


Module 1 - Supervised vs Unsupervised Learning
  • Machine Learning vs Statistical Modelling
  • Supervised vs Unsupervised Learning 
  • Supervised Learning Classification 
  • Unsupervised Learning 
Module 2 - Supervised Learning I
  • K-Nearest Neighbors 
  • Decision Trees 
  • Random Forests
  • Reliability of Random Forests 
  • Advantages & Disadvantages of Decision Trees 
 Module 3 - Supervised Learning II
  • Regression Algorithms 
  • Model Evaluation 
  • Model Evaluation: Overfitting & Underfitting
  • Understanding Different Evaluation Models 
 Module 4 - Unsupervised Learning
  • K-Means Clustering plus Advantages & Disadvantages 
  • Hierarchical Clustering plus Advantages & Disadvantages 
  • Measuring the Distances Between Clusters - Single Linkage Clustering 
  • Measuring the Distances Between Clusters - Algorithms for Hierarchy Clustering
  • Density-Based Clustering 
Module 5 - Dimensionality Reduction & Collaborative Filtering
  • Dimensionality Reduction: Feature Extraction & Selection 
  • Collaborative Filtering & Its Challenges 



  • Python for data science


  • You have to do hands-on lab for this course. The tool that you use for hands-on is called Jupyter and it is one of the most popular tools used by data scientists. If you are not familiar with Jupyter, I would recommend that you take our free Data Science Hands-on with Open Source Tools.
  • This hands-on lab requires that you have working knowledge of Python programming language as it applies to data analytics. If you don't feel you have sufficient skill in Data Analysis with Python, I recommend you take Data Analysis with Python courses.