From 3d347b63b1ef724f3732adff4be4ea80de3cb208 Mon Sep 17 00:00:00 2001 From: Jen Looper Date: Tue, 3 May 2022 13:20:07 -0400 Subject: [PATCH] enhancing the 'for teachers' area --- for-teachers.md | 43 ++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 42 insertions(+), 1 deletion(-) diff --git a/for-teachers.md b/for-teachers.md index 44b3bc8..f11ded4 100644 --- a/for-teachers.md +++ b/for-teachers.md @@ -18,6 +18,47 @@ If you prefer a more private format, ask your students to fork the curriculum, l There are many ways to make this work in an online classroom format. Please let us know what works best for you! +## Included in this curriculum: + +20 lessons, 40 quizzes, and 20 assignments. Sketchnotes accompany the lessons for visual learners. Many lessons are available in both Python and R and can be completed using Jupyter notebooks in VS Code. Learn more about how to set up your classroom to use this tech stack: https://code.visualstudio.com/docs/datascience/jupyter-notebooks. + +All sketchnotes, including a large-format poster, are in [this folder](./sketchnotes/). + +The entire curriculum is available [as a PDF](./pdf/readme.pdf). + +You can also run this curriculum as a standalone, offline-friendly web site by using [Docsify](https://docsify.js.org/#/). [Install Docsify](https://docsify.js.org/#/quickstart) on your local machine, then in the root folder of your local copy of this repo, type `docsify serve`. The website will be served on port 3000 on your localhost: `localhost:3000`. + +An offline-friendly version of the curriculum will open as a standalone web page: https://localhost:3000 + +Lessons are grouped into 6 parts: + +- 1: Introduction + - 1: Defining Data Science + - 2: Ethics + - 3: Defining Data + - 4: Probability and Statistics Overview +- 2: Working with Data + - 5: Relational Databases + - 6: Non-Relational Databases + - 7: Python + - 8: Data Preparation +- 3: Data Visualization + - 9: Visualization of Quantities + - 10: Visualization of Distributions + - 11: Visualization of Proportions + - 12: Visualization of Relationships + - 13: Meaningful Visualizations +- 4: Data Science Lifecycle + - 14: Introduction + - 15: Analyzing + - 16: Communication +- 5: Data Science in the Cloud + - 17: Introduction + - 18: Low-Code Options + - 19: Azure +- 6: Data Science in the Wild + - 20: Overview + ## 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! +We want to make this curriculum work for you and your students. Please give us feedback in the discussion boards! Feel free to create a classroom area on the discussion boards for your students.