This repository provides a comprehensive 12-week curriculum on classic Machine Learning for beginners, focusing on practical application using Scikit-learn and avoiding deep learning. It targets individuals new to ML, offering 26 lessons with quizzes, hands-on projects, and real-world data from diverse global cultures.

How It Works

The curriculum employs a project-based pedagogy, integrating learning with building. Each lesson includes pre- and post-lecture quizzes for reinforcement, written instructions, solution code, and assignments. A unique thematic approach uses global cultural data to illustrate ML concepts, enhancing engagement and retention. Lessons are primarily in Python, with many also available in R using R Markdown for integrated code, output, and narrative.

Quick Start & Requirements

• Installation: Fork the repository and clone it locally.
• Prerequisites: Python, Scikit-learn. R and R Markdown for R lessons.
• Resources: Links to Microsoft Learn modules, video walkthroughs on YouTube, and a PDF version of the curriculum are provided. The quiz app can be run locally.

Highlighted Details

• 12-week, 26-lesson structure with 52 quizzes.
• Project-based learning with real-world, culturally diverse datasets.
• Covers regression, classification, clustering, NLP, time series, and reinforcement learning.
• Python and R language support.

Maintenance & Community

Developed by Microsoft Cloud Advocates with contributions from authors, illustrators, and Microsoft Student Ambassadors. Links to contributing guidelines and a discussion board are available.

Licensing & Compatibility

The repository is licensed under the MIT License, permitting commercial use and integration with closed-source projects.

Limitations & Caveats

This curriculum focuses exclusively on "classic" ML techniques and does not cover deep learning, which is addressed in a separate Microsoft curriculum.