file edits for DS curriculum

pull/10/head
Jen Looper 3 years ago
parent 7d204e5793
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---
name: Bug report
about: Create a report to help us improve
title: ''
labels: ''
assignees: ''
---
**Describe the bug**
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Steps to reproduce the behavior:
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---
name: Feature request
about: Suggest an idea for this project
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labels: ''
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**Is your feature request related to a problem? Please describe.**
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## Track translation progress by opening a draft PR using this template and checking off the translations completed
Each lesson includes a translation of the README.md and the Assignment.md file, if available. Only mark the lesson complete if both those files are translated per lesson, please.
- [ ] 1
- [ ] 1-1
- [ ] 1-2
- [ ] 1-3
- [ ] 2
- [ ] 2-1
- [ ] 2-2
- [ ] 2-3
- [ ] 2-4
- [ ] 3
- [ ] 3-1
- [ ] 3-2
- [ ] 3-3
- [ ] 4
- [ ] 4-1
- [ ] 5
- [ ] 5-1
- [ ] 5-2
- [ ] 5-3
- [ ] 6
- [ ] 6-1
- [ ] 6-2
- [ ] 6-3
- [ ] 6-4
- [ ] 6-5
- [ ] 6-6
- [ ] 7
- [ ] 7-1
- [ ] 7-2
- [ ] 7-3
- [ ] 7-4
- [ ] Quiz (add a file in the quiz-app with all localizations)

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# Contributing
This project welcomes contributions and suggestions. Most contributions require you to
agree to a Contributor License Agreement (CLA) declaring that you have the right to,
and actually do, grant us the rights to use your contribution. For details, visit
https://cla.microsoft.com.
When you submit a pull request, a CLA-bot will automatically determine whether you need
to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the
instructions provided by the bot. You will only need to do this once across all repositories using our CLA.
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/)
or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.

@ -10,9 +10,9 @@ Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson cur
> **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.
[![Promo video](screenshot.png)]( "Promo video")
<!--[![Promo video](screenshot.png)]( "Promo video")
> 🎥 Click the image above for a video about the project the folks who created it!
> 🎥 Click the image above for a video about the project the folks who created it!-->
## Pedagogy
@ -36,36 +36,36 @@ In addition, a low-stakes quiz before a class sets the intention of the student
- assignment
- post-lesson quiz
> **A note about quizzes**: All quizzes are contained [in this app](), 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.
> **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.
## Lessons
| | Project Name | Concepts Taught | Learning Objectives | Linked Lesson | Author |
| :---: | :------------------------------------------------------: | :--------------------------------------------------------------------: | ----------------------------------------------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------: | :---------------------: |
| 01 | Defining Data Science | TBD | | | |
| 02 | Data Science Ethics | TBD | | | |
| 03 | Defining Data | TBD | | | |
| 04 | Introduction to Statistics Probability | TBD | | | |
| 05 | Working with Data | Spreadsheets | | | |
| 06 | Working with Data | Relational Databases | | | |
| 07 | Working with Data | NoSQL | | | |
| 08 | Working with Data | Python Data | | | |
| 09 | Working with Data | Cleaning Transformations | | | |
| 10 | Visualizing Data | Quantities | | | |
| 11 | Visualizing Data | Distributions | | | |
| 12 | Visualizing Data | Proportions | | | |
| 13 | Visualizing Data | Relationships | | | |
| 14 | Visualizing Data | Making meaningful visualizations | | | |
| 15 | The Data Science Lifecycle | Capturing | | | |
| 16 | The Data Science Lifecycle | Processing | | | |
| 17 | The Data Science Lifecycle | Analyzing | | | |
| 18 | The Data Science Lifecycle | Communication | | | |
| 19 | The Data Science Lifecycle | Maintaining | | | |
| 20 | Data Science in the Cloud | TBD | | | |
| 21 | Data Science in the Cloud | TBD | | | |
| 22 | Data Science in the Cloud | TBD | | | |
| 23 | Data Science in the Wild | TBD | | | |
| 24 | Data Science in the Wild | TBD | | | |
| | Project Name | Concepts Taught | Learning Objectives | Linked Lesson | Author |
| :---: | :-------------------------------------: | :------------------------------: | ------------------- | :-----------: | :----: |
| 01 | Defining Data Science | TBD | | | |
| 02 | Data Science Ethics | TBD | | | |
| 03 | Defining Data | TBD | | | |
| 04 | Introduction to Statistics Probability | TBD | | | |
| 05 | Working with Data | Spreadsheets | | | |
| 06 | Working with Data | Relational Databases | | | |
| 07 | Working with Data | NoSQL | | | |
| 08 | Working with Data | Python Data | | | |
| 09 | Working with Data | Cleaning Transformations | | | |
| 10 | Visualizing Data | Quantities | | | |
| 11 | Visualizing Data | Distributions | | | |
| 12 | Visualizing Data | Proportions | | | |
| 13 | Visualizing Data | Relationships | | | |
| 14 | Visualizing Data | Making meaningful visualizations | | | |
| 15 | The Data Science Lifecycle | Capturing | | | |
| 16 | The Data Science Lifecycle | Processing | | | |
| 17 | The Data Science Lifecycle | Analyzing | | | |
| 18 | The Data Science Lifecycle | Communication | | | |
| 19 | The Data Science Lifecycle | Maintaining | | | |
| 20 | Data Science in the Cloud | TBD | | | |
| 21 | Data Science in the Cloud | TBD | | | |
| 22 | Data Science in the Cloud | TBD | | | |
| 23 | Data Science in the Wild | TBD | | | |
| 24 | Data Science in the Wild | TBD | | | |
## Offline access

@ -1,25 +1,12 @@
# TODO: The maintainer of this repo has not yet edited this file
**REPO OWNER**: Do you want Customer Service & Support (CSS) support for this product/project?
- **No CSS support:** Fill out this template with information about how to file issues and get help.
- **Yes CSS support:** Fill out an intake form at [aka.ms/spot](https://aka.ms/spot). CSS will work with/help you to determine next steps. More details also available at [aka.ms/onboardsupport](https://aka.ms/onboardsupport).
- **Not sure?** Fill out a SPOT intake as though the answer were "Yes". CSS will help you decide.
*Then remove this first heading from this SUPPORT.MD file before publishing your repo.*
# Support
## How to file issues and get help
This project uses GitHub Issues to track bugs and feature requests. Please search the existing
issues before filing new issues to avoid duplicates. For new issues, file your bug or
feature request as a new Issue.
For help and questions about using this project, please **REPO MAINTAINER: INSERT INSTRUCTIONS HERE
FOR HOW TO ENGAGE REPO OWNERS OR COMMUNITY FOR HELP. COULD BE A STACK OVERFLOW TAG OR OTHER
CHANNEL. WHERE WILL YOU HELP PEOPLE?**.
For help and questions about using this project, file an issue.
## Microsoft Support Policy
Support for this **PROJECT or PRODUCT** is limited to the resources listed above.
Support for this repository is limited to the resources listed above.

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- Introduction TBD
- [Introduction to Machine Learning](../1-Introduction/1-intro-to-ML/README.md)
- [History of Machine Learning](../1-Introduction/2-history-of-ML/README.md)
- [ML and Fairness](../1-Introduction/3-fairness/README.md)
- [Techniques of ML](../1-Introduction/4-techniques-of-ML/README.md)

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module.exports = {
contents: ['docs/_sidebar.md'], // array of "table of contents" files path
pathToPublic: 'pdf/readme.pdf', // path where pdf will stored
pdfOptions: {
margin: { top: '100px', bottom: '100px' }
}, // reference: https://github.com/GoogleChrome/puppeteer/blob/master/docs/api.md#pagepdfoptions
removeTemp: true, // remove generated .md and .html or not
emulateMedia: 'print', // mediaType, emulating by puppeteer for rendering pdf, 'print' by default (reference: https://github.com/GoogleChrome/puppeteer/blob/master/docs/api.md#pageemulatemediamediatype)
};

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## For Educators
Would you like to use this curriculum in your classroom? Please feel free!
In fact, you can use it within GitHub itself by using GitHub Classroom.
To do that, fork this repo. You are going to need to create a repo for each lesson, so you're going to need to extract each folder into a separate repo. That way, [GitHub Classroom](https://classroom.github.com/classrooms) can pick up each lesson separately.
These [full instructions](https://github.blog/2020-03-18-set-up-your-digital-classroom-with-github-classroom/) will give you an idea how to set up your classroom.
## Using the repo as is
If you would like to use this repo as it currently stands, without using GitHub Classroom, that can be done as well. You would need to communicate with your students which lesson to work through together.
In an online format (Zoom, Teams, or other) you might form breakout rooms for the quizzes, and mentor students to help them get ready to learn. Then invite students to for the quizzes and submit their answers as 'issues' at a certain time. You might do the same with assignments, if you want students to work collaboratively out in the open.
If you prefer a more private format, ask your students to fork the curriculum, lesson by lesson, to their own GitHub repos as private repos, and give you access. Then they can complete quizzes and assignments privately and submit them to you via issues on your classroom repo.
There are many ways to make this work in an online classroom format. Please let us know what works best for you!
## Please give us your thoughts!
We want to make this curriculum work for you and your students. Please give us feedback in the discussion boards!

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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Data Science for Beginners</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1" />
<meta name="description" content="Description">
<meta name="viewport"
content="width=device-width, user-scalable=no, initial-scale=1.0, maximum-scale=1.0, minimum-scale=1.0">
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/docsify-themeable@0/dist/css/theme-simple.css">
</head>
<body>
<div id="app"></div>
<script>
window.$docsify = {
name: 'Data Science for Beginners',
repo: 'https://github.com/Microsoft/Data-Science-For-Beginners',
relativePath: true
}
</script>
<script src="//cdn.jsdelivr.net/npm/docsify/lib/docsify.min.js"></script>
</body>
</html>

2251
package-lock.json generated

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{
"name": "ml-for-beginners",
"version": "1.0.0",
"description": "Machine Learning for Beginners - A Curriculum",
"main": "index.js",
"scripts": {
"convert": "node_modules/.bin/docsify-to-pdf"
},
"repository": {
"type": "git",
"url": "git+https://github.com/microsoft/ML-For-Beginners.git"
},
"keywords": [
"machine",
"learning",
"ml",
"ai",
"curriculum"
],
"author": "Jen Looper and team",
"license": "MIT",
"bugs": {
"url": "https://github.com/microsoft/ML-For-Beginners/issues"
},
"homepage": "https://github.com/microsoft/ML-For-Beginners#readme",
"devDependencies": {
"docsify-to-pdf": "0.0.5"
}
}

@ -1,6 +1,6 @@
# Quizzes
These quizzes are the pre- and post-lecture quizzes for the web development for ml curriculum at https://aka.ms/ml-beginners
These quizzes are the pre- and post-lecture quizzes for the data sccience curriculum at https://aka.ms/datascience-beginners
## Project setup

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<!--add all root file translations here-->
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