Machine Learning using Python (2 days)

Online Campus

Online
Anywhere
Online

Past Locations for this Workshop Series

Machine Learning using Python (2 days) | Online

Online Campus

Online
Anywhere
Online

Past Locations for this Workshop Series

About this workshop series

This two day workshop will introduce students to data exploration and machine learning techniques. Students will learn about the data science workflow and will practice exploring and visualising data using Python and built-in libraries. Students will also explore the differences between supervised and unsupervised learning techniques and practice creating predictive regression models.

Day 1 - Developing the Fundamentals

Module 1: Introduction to Machine Learning (2.5 hours)

  • What is machine learning?
  • Installation and update of tools
  • Machine learning algorithms
  • Module 2: Exploring and using data sets (2.5 hours)

  • Learn the steps to pre-process a dataset and prepare it for machine learning algorithms
  • Day 2 - Diving into machine learning

    Module 3: Supervised vs. unsupervised learning (2.5 hours)

  • Review of machine learning algorithms
  • Classification, linear regression and logistic regression
  • Random forests, clustering
  • Decision trees
  • Module 4: Model Evaluation (2.5 hours)

  • Feature Engineering and Model Selection
  • Model Evaluation Metrics - Accuracy, RMSE, ROC, AUC, Confusion Matrix, Precision, Recall, F1 Score
  • Overfitting and Bias-Variance trade-off
  • Cross Validation
  • Takeaways

    After this lesson, you will be able to:

  • Collect data from a variety of sources (e.g., Excel, web-scraping, APIs and others)
  • Explore large data sets
  • Clean and "munge" the data to prepare it for analysis
  • Apply machine learning algorithms to gain insight from the data
  • Visualize the results of your analysis
  • Build your own library and Python scripts
  • Prereqs & Preparation

    Beginner/intermediate. This workshop is for analysts, product managers, mathematicians, business managers or anyone else that wants to learn about machine learning. A background in computer science, programming, and/or statistics is preferred for this workshop. It is not required but you are expected to be somewhat familiar with the command line tools and how to write simple programs. Recommended that you take the “Python for Beginners” workshop prior to attending this.

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