@ -104,9 +104,9 @@ The first step is to collect the data. While in many cases it can be a straight
</dd>
<dt>2) Data Storage</dt>
<dd>
Storing data can be challenging, especially if we are talking about big data. When deciding how to store data, it makes sense to anticipate the way you would to query the data in the future. There are several ways data can be stored:
Storing data can be challenging, especially if we are talking about big data. When deciding how to store data, it makes sense to anticipate the way you would like to query the data in the future. There are several ways data can be stored:
<ul>
<li>A relational database stores a collection of tables, and uses a special language called SQL to query them. Typically, tables are organized into different groups called schemas. In many cases we need to convert the data from original form to fit the schema.</li>
<li>A relational database stores a collection of tables, and uses a special language called SQL to query them. Typically, tables are organized into different groups called schemas. In many cases we need to convert the data from original form to fit the schema.</li>
<li><ahref="https://en.wikipedia.org/wiki/NoSQL">A NoSQL</a> database, such as <ahref="https://azure.microsoft.com/services/cosmos-db/?WT.mc_id=academic-77958-bethanycheum">CosmosDB</a>, does not enforce schemas on data, and allows storing more complex data, for example, hierarchical JSON documents or graphs. However, NoSQL databases do not have the rich querying capabilities of SQL, and cannot enforce referential integrity, i.e. rules on how the data is structured in tables and governing the relationships between tables.</li>
<li><ahref="https://en.wikipedia.org/wiki/Data_lake">Data Lake</a> storage is used for large collections of data in raw, unstructured form. Data lakes are often used with big data, where all data cannot fit on one machine, and has to be stored and processed by a cluster of servers. <ahref="https://en.wikipedia.org/wiki/Apache_Parquet">Parquet</a> is the data format that is often used in conjunction with big data.</li>
@ -32,7 +32,7 @@ The word "ethics" comes from the [Greek word "ethikos"](https://en.wikipedia.org
**Ethics** is about the shared values and moral principles that govern our behavior in society. Ethics is based not on laws but on
widely accepted norms of what is "right vs. wrong". However, ethical considerations can influence corporate governance initiatives and government regulations that create more incentives for compliance.
**Data Ethics** is a [new branch of ethics](https://royalsocietypublishing.org/doi/full/10.1098/rsta.2016.0360#sec-1) that "studies and evaluates moral problems related to _data, algorithms and corresponding practices_". Here, **"data"** focuses on actions related to generation, recording, curation, processing dissemination, sharing,and usage, **"algorithms"** focuses on AI, agents, machine learning,and robots, and **"practices"** focuses on topics like responsible innovation, programming, hacking and ethics codes.
**Data Ethics** is a [new branch of ethics](https://royalsocietypublishing.org/doi/full/10.1098/rsta.2016.0360#sec-1) that "studies and evaluates moral problems related to _data, algorithms and corresponding practices_". Here, **"data"** focuses on actions related to generation, recording, curation, processing, dissemination, sharing,and usage, **"algorithms"** focuses on AI, agents, machine learning,and robots, and **"practices"** focuses on topics like responsible innovation, programming, hacking, and ethics codes.
**Applied Ethics** is the [practical application of moral considerations](https://en.wikipedia.org/wiki/Applied_ethics). It's the process of actively investigating ethical issues in the context of _real-world actions, products and processes_, and taking corrective measures to make that these remain aligned with our defined ethical values.
@ -60,7 +60,7 @@ Let's briefly explore these principles. _Transparency_ and _accountability_ are
* [**Privacy & Security**](https://www.microsoft.com/en-us/ai/responsible-ai?activetab=pivot1:primaryr6) - is about understanding data lineage, and providing _data privacy and related protections_ to users.
* [**Inclusiveness**](https://www.microsoft.com/en-us/ai/responsible-ai?activetab=pivot1:primaryr6) - is about designing AI solutions with intention, adapting them to meet a _broad range of human needs_& capabilities.
> 🚨 Think about what your data ethics mission statement could be. Explore ethical AI frameworks from other organizations - here are examples from [IBM](https://www.ibm.com/cloud/learn/ai-ethics), [Google](https://ai.google/principles),and [Facebook](https://ai.facebook.com/blog/facebooks-five-pillars-of-responsible-ai/). What shared values do they have in common? How do these principles relate to the AI product or industry they operate in?
> 🚨 Think about what your data ethics mission statement could be. Explore ethical AI frameworks from other organizations - here are examples from [IBM](https://www.ibm.com/cloud/learn/ai-ethics), [Google](https://ai.google/principles),and [Facebook](https://ai.facebook.com/blog/facebooks-five-pillars-of-responsible-ai/). What shared values do they have in common? How do these principles relate to the AI product or industry they operate in?
[](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=344191198)
@ -21,12 +23,26 @@ Azure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson cur
|:---:|
| Data Science For Beginners - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
## Announcement - New Curriculum on Generative AI was just released!
We just released a 12 lesson curriculum on generative AI. Come learn things like:
- prompting and prompt engineering
- text and image app generation
- search apps
As usual, there's a lesson, assignments to complete, knowledge checks and challenges.
Check it out:
> https://aka.ms/genai-beginners
# Are you a student?
Get started with the following resources:
- [Student Hub page](https://docs.microsoft.com/en-gb/learn/student-hub?WT.mc_id=academic-77958-bethanycheum) In this page, you will find beginner resources, Student packs and even ways to get a free cert voucher. This is one page you want to bookmark and check from time to time as we switch out content at least monthly.
- [Microsoft Learn Student Ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77958-bethanycheum) Join a global community of student ambassadors, this could be your way into Microsoft
- [Microsoft Learn Student Ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77958-bethanycheum) Join a global community of student ambassadors, this could be your way into Microsoft.
# Getting Started
@ -95,24 +111,48 @@ In addition, a low-stakes quiz before a class sets the intention of the student
| 18 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/README.md) | Training models using Low Code tools. |[lesson](5-Data-Science-In-Cloud/18-Low-Code/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) |
| 19 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/README.md) | Deploying models with Azure Machine Learning Studio. | [lesson](5-Data-Science-In-Cloud/19-Azure/README.md)| [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) |
| 20 | Data Science in the Wild | [In the Wild](6-Data-Science-In-Wild/README.md) | Data science driven projects in the real world. | [lesson](6-Data-Science-In-Wild/20-Real-World-Examples/README.md) | [Nitya](https://twitter.com/nitya) |
## GitHub Codespaces
Follow these steps to open this sample in a Codespace:
1. Click the Code drop-down menu and select the Open with Codespaces option.
2. Select + New codespace at the bottom on the pane.
For more info, check out the [GitHub documentation](https://docs.github.com/en/codespaces/developing-in-codespaces/creating-a-codespace-for-a-repository#creating-a-codespace).
## VSCode Remote - Containers
Follow these steps to open this repo in a container using your local machine and VSCode using the VS Code Remote - Containers extension:
1. If this is your first time using a development container, please ensure your system meets the pre-reqs (i.e. have Docker installed) in [the getting started documentation](https://code.visualstudio.com/docs/devcontainers/containers#_getting-started).
To use this repository, you can either open the repository in an isolated Docker volume:
**Note**: Under the hood, this will use the Remote-Containers: **Clone Repository in Container Volume...** command to clone the source code in a Docker volume instead of the local filesystem. [Volumes](https://docs.docker.com/storage/volumes/) are the preferred mechanism for persisting container data.
Or open a locally cloned or downloaded version of the repository:
- Clone this repository to your local filesystem.
- Press F1 and select the **Remote-Containers: Open Folder in Container...** command.
- Select the cloned copy of this folder, wait for the container to start, and try things out.
## Offline access
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`.
> Note, notebooks will not be rendered via Docsify, so when you need to run a notebook, do that separately in VS Code running a Python kernel.
## PDF
A PDF of all of the lessons can be found [here](https://microsoft.github.io/Data-Science-For-Beginners/pdf/readme.pdf)
## Help Wanted!
If you would like to translate all or part of the curriculum, please follow our [Translations](TRANSLATIONS.md) guide
If you would like to translate all or part of the curriculum, please follow our [Translations](TRANSLATIONS.md) guide.
## Other Curricula
Our team produces other curricula! Check out:
- [Machine Learning for Beginners](https://aka.ms/ml-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners?WT.mc_id=academic-113596-abartolo)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [Machine Learning for Beginners](https://aka.ms/ml-beginners)
- [XR Development for Beginners](https://aka.ms/xr-dev-for-beginners)
- [Mastering GitHub Copilot for AI Paired Programming](https://aka.ms/GitHubCopilotAI)
Angel Mendez
2 years ago
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