Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Data Science. Each lesson includes pre-lesson and post-lesson quizzes, written instructions to complete the lesson, a solution, and an assignment. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'.
> **Teachers**, we have [included some suggestions](for-teachers.md) on how to use this curriculum. We'd love your feedback [in our discussion forum]()!
> **Students**, to use this curriculum on your own, fork the entire repo complete the exercises on your own, starting with a pre-lecture quiz, then reading the lecture completing the rest of the activities. Try to create the projects by comprehending the lessons rather than copying the solution code; however that code is available in the /solutions folders in each project-oriented lesson. Another idea would be to form a study group with friends go through the content together. For further study, we recommend [Microsoft Learn]() by watching the videos mentioned below.
We have chosen two pedagogical tenets while building this curriculum: ensuring that it is project-based that it includes frequent quizzes. By the end of this series, students will have ...
In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible fun can be taken in whole or in part. The projects start small become increasingly complex by the end of the 12 week cycle.
> Find our [Code of Conduct](CODE_OF_CONDUCT.md), [Contributing](CONTRIBUTING.md), [Translation](TRANSLATIONS.md) guidelines. We welcome your constructive feedback!
>
## Each lesson includes:
- optional sketchnote
- optional supplemental video
- pre-lesson warmup quiz
- written lesson
- for project-based lessons, step-by-step guides on how to build the project
> **A note about quizzes**: All quizzes are contained [in this app](https://red-water-0103e7a0f.azurestaticapps.net/), for 48 total quizzes of three questions each. They are linked from within the lessons but the quiz app can be run locally; follow the instruction in the `quiz-app` folder. They are gradually being localized.
| 04 | Introduction to Statistics & Probability | [Introduction](1-Introduction/README.md) | TBD | | |
| 05 | Working with Spreadsheets | [Working With Data](2-Working-With-Data/README.md) | Spreadsheets | | |
| 06 | Working with Relational Databases | [Working With Data](2-Working-With-Data/README.md) | Relational Databases | | |
| 07 | Working with NoSQL Data | [Working With Data](2-Working-With-Data/README.md) | NoSQL | | |
| 08 | Working with Python | [Working With Data](2-Working-With-Data/README.md) | Python Data | | |
| 09 | Cleaning and Transforming Data | [Working With Data](2-Working-With-Data/README.md) | Cleaning Transformations | | |
| 10 | Visualizing Quantities | [Data Visualization](3-Data-Visualization/README.md) | Learn how to use Matplotlib to visualize bird data 🦆 | [Quantities](3-Data-Visualization/10-visualization-quantities/README.md) | Jen |
| 11 | Visualizing Distributions of Data | [Data Visualization](3-Data-Visualization/README.md) | Distributions | | Jen |
You can run this documentation offline by using [Docsify](https://docsify.js.org/#/). Fork this repo, [install Docsify](https://docsify.js.org/#/quickstart) on your local machine, then in the root folder of this repo, type `docsify serve`. The website will be served on port 3000 on your localhost: `localhost:3000`.
## PDF
A PDF of all of the lessons can be found [here](pdf/readme.pdf)
