10 Weeks, 20 Lessons, Data Science for All!
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README.md

Data Science for Beginners - A Curriculum

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'.

Hearty thanks to our authors:

Getting Started

Teachers, we have included some suggestions 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.

Pedagogy

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, Contributing, Translation 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
  • knowledge checks
  • a challenge
  • supplemental reading
  • 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.

Lessons

Lesson Number Topic Lesson Grouping Learning Objectives Linked Lesson Author
01 Defining Data Science Introduction TBD
02 Data Science Ethics Introduction Data Ethics Concepts, Challenges & Frameworks. Nitya Narasimhan
03 Defining Data Introduction TBD
04 Introduction to Statistics & Probability Introduction TBD
05 Working with Spreadsheets Working With Data Spreadsheets
06 Working with Relational Databases Working With Data Relational Databases
07 Working with NoSQL Data Working With Data NoSQL
08 Working with Python Working With Data Python Data
09 Cleaning and Transforming Data Working With Data Cleaning Transformations
10 Visualizing Quantities Data Visualization Learn how to use Matplotlib to visualize bird data 🦆 Quantities Jen
11 Visualizing Distributions of Data Data Visualization Distributions Jen
12 Visualizing Proportions Data Visualization Proportions Jen
13 Visualizing Relationships Data Visualization Relationships Jen
14 Meaningful Visualizations Data Visualization Making meaningful visualizations Jen
15 The Data Science Lifecycle Lifecycle Capturing
16 The Data Science Lifecycle Lifecycle Processing
17 The Data Science Lifecycle Lifecycle Analyzing
18 The Data Science Lifecycle Lifecycle Communication
19 The Data Science Lifecycle Lifecycle Maintaining
20 Data Science in the Cloud Cloud Data TBD
21 Data Science in the Cloud Cloud Data TBD
22 Data Science in the Cloud Cloud Data TBD
23 Data Science in the Wild In the Wild TBD
24 Data Science in the Wild In the Wild TBD

Offline access

You can run this documentation offline by using Docsify. Fork this repo, install Docsify 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