About Programming Languages: Lessons are mainly in Python, but many have R versions too. For R lessons, check the /solution folder for .rmd files (R Markdown). These combine code, outputs, and explanations in a single document - perfect for data science workflows. You can export to PDF, HTML, or Word formats.
Lesson Curriculum
| Lesson Number | Topic | Lesson Grouping | Learning Objectives | Linked Lesson | Author |
|---|---|---|---|---|---|
| 01 | Introduction to machine learning | Introduction | Learn the basic concepts behind machine learning | Lesson | Muhammad |
| 02 | The History of machine learning | Introduction | Learn the history underlying this field | Lesson | Jen and Amy |
| 03 | Fairness and machine learning | Introduction | What are the important philosophical issues around fairness that students should consider when building and applying ML models? | Lesson | Tomomi |
| 04 | Techniques for machine learning | Introduction | What techniques do ML researchers use to build ML models? | Lesson | Chris and Jen |
| 05 | Introduction to regression | Regression | Get started with Python and Scikit-learn for regression models | Python • R | Jen • Eric Wanjau |
| 06 | North American pumpkin prices 🎃 | Regression | Visualize and clean data in preparation for ML | Python • R | Jen • Eric Wanjau |
| 07 | North American pumpkin prices 🎃 | Regression | Build linear and polynomial regression models | Python • R | Jen and Dmitry • Eric Wanjau |
| 08 | North American pumpkin prices 🎃 | Regression | Build a logistic regression model | Python • R | Jen • Eric Wanjau |
| 09 | A Web App 🔌 | Web App | Build a web app to use your trained model | Python | Jen |
| 10 | Introduction to classification | Classification | Clean, prep, and visualize your data; introduction to classification | Python • R | Jen and Cassie • Eric Wanjau |
| 11 | Delicious Asian and Indian cuisines 🍜 | Classification | Introduction to classifiers | Python • R | Jen and Cassie • Eric Wanjau |
| 12 | Delicious Asian and Indian cuisines 🍜 | Classification | More classifiers | Python • R | Jen and Cassie • Eric Wanjau |
| 13 | Delicious Asian and Indian cuisines 🍜 | Classification | Build a recommender web app using your model | Python | Jen |
| 14 | Introduction to clustering | Clustering | Clean, prep, and visualize your data; Introduction to clustering | Python • R | Jen • Eric Wanjau |
| 15 | Exploring Nigerian Musical Tastes 🎧 | Clustering | Explore the K-Means clustering method | Python • R | Jen • Eric Wanjau |
| 16 | Introduction to natural language processing ☕️ | Natural language processing | Learn the basics about NLP by building a simple bot | Python | Stephen |
| 17 | Common NLP Tasks ☕️ | Natural language processing | Deepen your NLP knowledge by understanding common tasks required when dealing with language structures | Python | Stephen |
| 18 | Translation and sentiment analysis ♥️ | Natural language processing | Translation and sentiment analysis with Jane Austen | Python | Stephen |
| 19 | Romantic hotels of Europe ♥️ | Natural language processing | Sentiment analysis with hotel reviews 1 | Python | Stephen |
| 20 | Romantic hotels of Europe ♥️ | Natural language processing | Sentiment analysis with hotel reviews 2 | Python | Stephen |
| 21 | Introduction to time series forecasting | Time series | Introduction to time series forecasting | Python | Francesca |
| 22 | ⚡️ World Power Usage ⚡️ - time series forecasting with ARIMA | Time series | Time series forecasting with ARIMA | Python | Francesca |
| 23 | ⚡️ World Power Usage ⚡️ - time series forecasting with SVR | Time series | Time series forecasting with Support Vector Regressor | Python | Anirban |
| 24 | Introduction to reinforcement learning | Reinforcement learning | Introduction to reinforcement learning with Q-Learning | Python | Dmitry |
| 25 | Help Peter avoid the wolf! 🐺 | Reinforcement learning | Reinforcement learning Gym | Python | Dmitry |
| Postscript | Real-World ML scenarios and applications | ML in the Wild | Interesting and revealing real-world applications of classical ML | Lesson | Team |
| Postscript | Model Debugging in ML using RAI dashboard | ML in the Wild | Model Debugging in Machine Learning using Responsible AI dashboard components | Lesson | Ruth Yakubu |
find all additional resources for this course in our Microsoft Learn collection
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