diff --git a/1-Introduction/02-ethics/assignment.md b/1-Introduction/02-ethics/assignment.md index ec12ef18..f4ce3d1a 100644 --- a/1-Introduction/02-ethics/assignment.md +++ b/1-Introduction/02-ethics/assignment.md @@ -1,8 +1,21 @@ -## Title +## Write A Data Ethics Case Study ## Instructions +You've learned about various [Data Ethics Challenges](README?id=_2-ethics-challenges) and seen some examples of [Case Studies](README?id=_3-case-studies) reflecting data ethics challenges in real-world contexts. + +In this assignment, you'll write your own case study reflecting a data ethics challenge from your own experience, or from a relevant real-world context you are familiar with. Just follow these steps: + +1. `Pick a Data Ethics Challenge`. Look at the [the lesson examples](README?id=_2-ethics-challenges) or explore online examples like [the Deon Checklist](https://deon.drivendata.org/examples/) to get inspiration. + +2. `Describe a Real World Example`. Think about a situation you have heard of (headlines, research study etc.) or experienced (local community), where this specific challenge occurred. Think about the data ethics questions related to the challenge - and discuss the potential harms or unintended consequences that arise because of this issue. Bonus points: think about potential solutions or processes that may be applied here to help eliminate or mitigate the adverse impact of this challenge. + +3. `Provide a Related Resources list`. Share one or more resources (links to an article, a personal blog post or image, online research paper etc.) to prove this was a real-world occurrence. Bonus points: share resources that also showcase the potential harms & consequences from the incident, or highlight positive steps taken to prevent its recurrence. + + + ## Rubric Exemplary | Adequate | Needs Improvement --- | --- | -- | +One or more data ethics challenges are identified.

The case study clearly describes a real-world incident reflecting that challenge, and highlights undesirable consequences or harms it caused.

There is at least one linked resource to prove this occurred. | One data ethics challenge is identified.

At least one relevant harm or consequence is discussed briefly.

However discussion is limited or lacks proof of real-world occurence. | A data challenge is identified.

However the description or resources do not adequately reflect the challenge or prove it's real-world occurence. | diff --git a/2-Working-With-Data/06-non-relational/README.md b/2-Working-With-Data/06-non-relational/README.md index fea1a855..32bbc175 100644 --- a/2-Working-With-Data/06-non-relational/README.md +++ b/2-Working-With-Data/06-non-relational/README.md @@ -56,7 +56,7 @@ NoSQL is an umbrella term for the different ways to store non-relational data an [Document](https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data#document-data-stores) data stores build on the concept of a key-value data store and is made up of a series of fields and objects. This section will explore document databases with the Cosmos DB emulator. -A Cosmos DB database fits the definition of "Not Only SQL", where Cosmos DB's document database relies on SQL to query the data. The [previous lesson](2-Working-With-Data\06-non-relational) on SQL covers the basics of the language, and we'll be able to apply some of the same queries to a document database here. We'll be using the Cosmos DB Emulator, which allows us to create and explore a document database locally on a computer. Read more about the Emulator [here](https://docs.microsoft.com/en-us/azure/cosmos-db/local-emulator?tabs=ssl-netstd21). +A Cosmos DB database fits the definition of "Not Only SQL", where Cosmos DB's document database relies on SQL to query the data. The [previous lesson](../05-relational-databases/README.md) on SQL covers the basics of the language, and we'll be able to apply some of the same queries to a document database here. We'll be using the Cosmos DB Emulator, which allows us to create and explore a document database locally on a computer. Read more about the Emulator [here](https://docs.microsoft.com/en-us/azure/cosmos-db/local-emulator?tabs=ssl-netstd21). A document is a collection of fields and object values, where the fields describe what the object value represents. Below is an example of a document. diff --git a/3-Data-Visualization/13-meaningful-visualizations/starter/package-lock.json b/3-Data-Visualization/13-meaningful-visualizations/starter/package-lock.json index f777f9d0..9d5484a8 100644 --- a/3-Data-Visualization/13-meaningful-visualizations/starter/package-lock.json +++ b/3-Data-Visualization/13-meaningful-visualizations/starter/package-lock.json @@ -1715,7 +1715,6 @@ "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-4.3.0.tgz", "integrity": "sha512-zbB9rCJAT1rbjiVDb2hqKFHNYLxgtk8NURxZ3IZwD3F6NtxbXZQCnnSi1Lkx+IDohdPlFp222wVALIheZJQSEg==", "dev": true, - "optional": true, "requires": { "color-convert": "^2.0.1" } @@ -1747,11 +1746,10 @@ } }, "chalk": { - "version": "4.1.0", - "resolved": "https://registry.npmjs.org/chalk/-/chalk-4.1.0.tgz", - "integrity": "sha512-qwx12AxXe2Q5xQ43Ac//I6v5aXTipYrSESdOgzrN+9XjgEpyjpKuvSGaN4qE93f7TQTlerQQ8S+EQ0EyDoVL1A==", + "version": "4.1.2", + "resolved": "https://registry.npmjs.org/chalk/-/chalk-4.1.2.tgz", + "integrity": "sha512-oKnbhFyRIXpUuez8iBMmyEa4nbj4IOQyuhc/wy9kY7/WVPcwIO9VA668Pu8RkO7+0G76SLROeyw9CpQ061i4mA==", "dev": true, - 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"optional": true, "requires": { "big.js": "^5.2.2", "emojis-list": "^3.0.0", @@ -1814,7 +1808,6 @@ "resolved": "https://registry.npmjs.org/supports-color/-/supports-color-7.2.0.tgz", "integrity": "sha512-qpCAvRl9stuOHveKsn7HncJRvv501qIacKzQlO/+Lwxc9+0q2wLyv4Dfvt80/DPn2pqOBsJdDiogXGR9+OvwRw==", "dev": true, - "optional": true, "requires": { "has-flag": "^4.0.0" } @@ -1837,11 +1830,10 @@ } }, "vue-loader-v16": { - "version": "npm:vue-loader@16.1.2", - "resolved": "https://registry.npmjs.org/vue-loader/-/vue-loader-16.1.2.tgz", - "integrity": "sha512-8QTxh+Fd+HB6fiL52iEVLKqE9N1JSlMXLR92Ijm6g8PZrwIxckgpqjPDWRP5TWxdiPaHR+alUWsnu1ShQOwt+Q==", + "version": "npm:vue-loader@16.8.1", + "resolved": "https://registry.npmjs.org/vue-loader/-/vue-loader-16.8.1.tgz", + "integrity": "sha512-V53TJbHmzjBhCG5OYI2JWy/aYDspz4oVHKxS43Iy212GjGIG1T3EsB3+GWXFm/1z5VwjdjLmdZUFYM70y77vtQ==", "dev": true, - "optional": true, "requires": { "chalk": "^4.1.0", "hash-sum": "^2.0.0", @@ -3394,9 +3386,9 @@ "dev": true }, "color-string": { - "version": "1.5.4", - "resolved": "https://registry.npmjs.org/color-string/-/color-string-1.5.4.tgz", - "integrity": "sha512-57yF5yt8Xa3czSEW1jfQDE79Idk0+AkN/4KWad6tbdxUmAs3MvjxlWSWD4deYytcRfoZ9nhKyFl1kj5tBvidbw==", + "version": "1.6.0", + "resolved": "https://registry.npmjs.org/color-string/-/color-string-1.6.0.tgz", + "integrity": "sha512-c/hGS+kRWJutUBEngKKmk4iH3sD59MBkoxVapS/0wgpCz2u7XsNloxknyvBhzwEs1IbV36D9PwqLPJ2DTu3vMA==", "dev": true, "requires": { "color-name": "^1.0.0", @@ -4461,9 +4453,9 @@ "dev": true }, "dns-packet": { - "version": "1.3.1", - "resolved": "https://registry.npmjs.org/dns-packet/-/dns-packet-1.3.1.tgz", - "integrity": "sha512-0UxfQkMhYAUaZI+xrNZOz/as5KgDU0M/fQ9b6SpkyLbk3GEswDi6PADJVaYJradtRVsRIlF1zLyOodbcTCDzUg==", + "version": "1.3.4", + "resolved": "https://registry.npmjs.org/dns-packet/-/dns-packet-1.3.4.tgz", + "integrity": "sha512-BQ6F4vycLXBvdrJZ6S3gZewt6rcrks9KBgM9vrhW+knGRqc8uEdT7fuCwloc7nny5xNoMJ17HGH0R/6fpo8ECA==", "dev": true, "requires": { "ip": "^1.1.0", @@ -7506,6 +7498,12 @@ "dev": true, "optional": true }, + "nanocolors": { + "version": "0.2.11", + "resolved": "https://registry.npmjs.org/nanocolors/-/nanocolors-0.2.11.tgz", + "integrity": "sha512-83ttyvfJj66dKMadWfBkEUOEDFfRc8FpzTJvh1MySR/pzWFmFikTQZGOV6kHZRz7yR/heiQ1y/MHBBN5P/e7WQ==", + "dev": true + }, "nanomatch": { "version": "1.2.13", "resolved": "https://registry.npmjs.org/nanomatch/-/nanomatch-1.2.13.tgz", @@ -8109,9 +8107,9 @@ "dev": true }, "path-parse": { - 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"supports-color": "^6.1.0" + "nanocolors": "^0.2.2", + "source-map": "^0.6.1" }, "dependencies": { "source-map": { @@ -8246,15 +8243,6 @@ "resolved": "https://registry.npmjs.org/source-map/-/source-map-0.6.1.tgz", "integrity": "sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g==", "dev": true - }, - "supports-color": { - "version": "6.1.0", - "resolved": "https://registry.npmjs.org/supports-color/-/supports-color-6.1.0.tgz", - "integrity": "sha512-qe1jfm1Mg7Nq/NSh6XE24gPXROEVsWHxC1LIx//XNlD9iw7YZQGjZNjYN7xGaEG6iKdA8EtNFW6R0gjnVXp+wQ==", - "dev": true, - "requires": { - "has-flag": "^3.0.0" - } } } }, @@ -10862,9 +10850,9 @@ } }, "url-parse": { - "version": "1.4.7", - "resolved": "https://registry.npmjs.org/url-parse/-/url-parse-1.4.7.tgz", - "integrity": "sha512-d3uaVyzDB9tQoSXFvuSUNFibTd9zxd2bkVrDRvF5TmvWWQwqE4lgYJ5m+x1DbecWkw+LK4RNl2CU1hHuOKPVlg==", + "version": "1.5.3", + "resolved": "https://registry.npmjs.org/url-parse/-/url-parse-1.5.3.tgz", + "integrity": "sha512-IIORyIQD9rvj0A4CLWsHkBBJuNqWpFQe224b6j9t/ABmquIS0qDU2pY6kl6AuOrL5OkCXHMCFNe1jBcuAggjvQ==", "dev": true, "requires": { "querystringify": "^2.1.1", @@ -11831,9 +11819,9 @@ } }, "ws": { - "version": "6.2.1", - "resolved": "https://registry.npmjs.org/ws/-/ws-6.2.1.tgz", - "integrity": "sha512-GIyAXC2cB7LjvpgMt9EKS2ldqr0MTrORaleiOno6TweZ6r3TKtoFQWay/2PceJ3RuBasOHzXNn5Lrw1X0bEjqA==", + "version": "6.2.2", + "resolved": "https://registry.npmjs.org/ws/-/ws-6.2.2.tgz", + "integrity": "sha512-zmhltoSR8u1cnDsD43TX59mzoMZsLKqUweyYBAIvTngR3shc0W6aOZylZmq/7hqyVxPdi+5Ud2QInblgyE72fw==", "dev": true, "requires": { "async-limiter": "~1.0.0" diff --git a/4-Data-Science-Lifecycle/15-analyzing/README.md b/4-Data-Science-Lifecycle/15-analyzing/README.md index e51398c3..f397ed93 100644 --- a/4-Data-Science-Lifecycle/15-analyzing/README.md +++ b/4-Data-Science-Lifecycle/15-analyzing/README.md @@ -40,8 +40,6 @@ You don’t have to wait until the data is thoroughly cleaned and analyzed to st All the topics in this lesson can help identify missing or inconsistent values, but Pandas provides functions to check for some of these. [isna() or isnull()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.isna.html) can check for missing values. One important piece of exploring for these values within your data is to explore why they ended up that way in the first place. This can help you decide on what [actions to take to resolve them](2-Working-With-Data\08-data-preparation\notebook.ipynb). -## 🚀 Challenge - ## [Pre-Lecture Quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/27) ## Assignment diff --git a/4-Data-Science-Lifecycle/16-communication/README.md b/4-Data-Science-Lifecycle/16-communication/README.md index 4ef7de84..9877ff38 100644 --- a/4-Data-Science-Lifecycle/16-communication/README.md +++ b/4-Data-Science-Lifecycle/16-communication/README.md @@ -26,6 +26,7 @@ Throughout this lesson two different types of communication will be discussed, O When communicating data, there will be cases where you will be using one-way communication (think about presenting at a conference, or to a large group where questions won’t be asked directly after) and there will be cases where you will use two-way communication (think about using data to persuade a few stakeholders for buy-in, or to convince a teammate that time and effort should be spent building something new). # Effective Communication + ### Your Responsibilities as a communicator When communicating, it is your job to make sure that your receiver(s) are taking away the information that you want them to take away. When you’re communicating data, you don’t just want your receivers to takeaway numbers, you want your receivers to takeaway a story that’s informed by your data. A good data communicator is a good storyteller. @@ -170,9 +171,8 @@ If Emerson took approach #2, it is much more likely that the team leads will tak - Approach it Like an Actual Story - Use Meaningful Words & Phrases - Use Emotion -### Post Lecture Quiz - +## [Post-Lecture Quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/31) ### Recommended Resources for Self Study [The Five C's of Storytelling - Articulate Persuasion](http://articulatepersuasion.com/the-five-cs-of-storytelling/) @@ -213,8 +213,6 @@ If Emerson took approach #2, it is much more likely that the team leads will tak [1. Communicating Data - Communicating Data with Tableau [Book] (oreilly.com)](https://www.oreilly.com/library/view/communicating-data-with/9781449372019/ch01.html) +## Assignment - -## [Post-Lecture Quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/31) - -Review what you've just learned with the Post-Lecture Quiz above! +[Tell a story](assignment.md) diff --git a/4-Data-Science-Lifecycle/16-communication/assignment.md b/4-Data-Science-Lifecycle/16-communication/assignment.md index b7af6412..2bcb5dd1 100644 --- a/4-Data-Science-Lifecycle/16-communication/assignment.md +++ b/4-Data-Science-Lifecycle/16-communication/assignment.md @@ -1,8 +1,12 @@ -# Title +# Tell a story ## Instructions +Data Science is all about storytelling. Pick any dataset and write a short paper about a story you could tell about it. What do you hope your dataset can reveal? What will you do if its revelations prove problematic? What if your data doesn't easily unlock its secrets? Think of the scenarios your dataset might present and write them down. + ## Rubric Exemplary | Adequate | Needs Improvement --- | --- | -- | + +A one-page essay is presented in .doc format with the dataset explained, documented, credited, and a coherent story is presented about it with detailed examples from the data.| A shorter essay is presented in less detailed format | The essay is found lacking in one of the above details. \ No newline at end of file diff --git a/4-Data-Science-Lifecycle/16-communication/notebook.ipynb b/4-Data-Science-Lifecycle/16-communication/notebook.ipynb deleted file mode 100644 index e69de29b..00000000 diff --git a/4-Data-Science-Lifecycle/16-communication/solution/notebook.ipynb b/4-Data-Science-Lifecycle/16-communication/solution/notebook.ipynb deleted file mode 100644 index e69de29b..00000000 diff --git a/4-Data-Science-Lifecycle/assignment.md b/4-Data-Science-Lifecycle/assignment.md deleted file mode 100644 index b7af6412..00000000 --- a/4-Data-Science-Lifecycle/assignment.md +++ /dev/null @@ -1,8 +0,0 @@ -# Title - -## Instructions - -## Rubric - -Exemplary | Adequate | Needs Improvement ---- | --- | -- | diff --git a/5-Data-Science-In-Cloud/17-Introduction/README.md b/5-Data-Science-In-Cloud/17-Introduction/README.md index bf2ab48e..f4455a97 100644 --- a/5-Data-Science-In-Cloud/17-Introduction/README.md +++ b/5-Data-Science-In-Cloud/17-Introduction/README.md @@ -28,8 +28,6 @@ Most cloud computing services fall into three categories: Infrastructure as a Se * Software as a Service (SaaS): users get access to software applications over the Internet, on demand and typically on a subscription basis. Users don’t need to worry about hosting and managing the software application, the underlying infrastructure or the maintenance, like software upgrades and security patching. Some of the largest Cloud providers are Amazon Web Services, Google Cloud Platform and Microsoft Azure. - - ## Why Choose the Cloud for Data Science? Developers and IT professionals chose to work with the Cloud for many reasons, including the following: @@ -71,8 +69,6 @@ The steps necessary to create this project are as follows: * Start the job To view the full process, check out the [documentation](https://docs.microsoft.com/azure/stream-analytics/stream-analytics-twitter-sentiment-analysis-trends?WT.mc_id=academic-40229-cxa&ocid=AID30411099). - - ### Scientific papers analysis Let’s take another example of a project created by [Dmitry Soshnikov](http://soshnikov.com), one of the authors of this curriculum. @@ -87,8 +83,6 @@ Let's see the different steps used for this: To see the full process, visit [Dmitry’s blog](https://soshnikov.com/science/analyzing-medical-papers-with-azure-and-text-analytics-for-health/). As you can see, we can leverage Cloud services in many ways to perform Data Science. - - ## Footnote Sources: @@ -99,3 +93,7 @@ Sources: ## Post-Lecture Quiz [Post-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/33) + +## Assignment + +[Market Research](assignment.md) diff --git a/5-Data-Science-In-Cloud/17-Introduction/assignment.md b/5-Data-Science-In-Cloud/17-Introduction/assignment.md index b7af6412..a12beec5 100644 --- a/5-Data-Science-In-Cloud/17-Introduction/assignment.md +++ b/5-Data-Science-In-Cloud/17-Introduction/assignment.md @@ -1,8 +1,10 @@ -# Title +# Market Research ## Instructions +In this lesson you learned that there are several important cloud providers. Do some market research to discover what each can offer to the Data Scientist. Are the offerings comparable? Write a paper to describe the offerings of three or more of these cloud providers. ## Rubric Exemplary | Adequate | Needs Improvement --- | --- | -- | +A one page paper describes three cloud providers' data science offerings and differentiates between them. | A shorter paper is presented | A paper is presented without completing the analysis \ No newline at end of file diff --git a/5-Data-Science-In-Cloud/17-Introduction/notebook.ipynb b/5-Data-Science-In-Cloud/17-Introduction/notebook.ipynb deleted file mode 100644 index e69de29b..00000000 diff --git a/5-Data-Science-In-Cloud/17-Introduction/solution/notebook.ipynb b/5-Data-Science-In-Cloud/17-Introduction/solution/notebook.ipynb deleted file mode 100644 index e69de29b..00000000 diff --git a/5-Data-Science-In-Cloud/18-Low-Code/notebook.ipynb b/5-Data-Science-In-Cloud/18-Low-Code/notebook.ipynb deleted file mode 100644 index e69de29b..00000000 diff --git a/5-Data-Science-In-Cloud/18-Low-Code/solution/notebook.ipynb b/5-Data-Science-In-Cloud/18-Low-Code/solution/notebook.ipynb deleted file mode 100644 index e69de29b..00000000 diff --git a/6-Data-Science-In-Wild/20-Real-World-Examples/README.md b/6-Data-Science-In-Wild/20-Real-World-Examples/README.md index bdba25a1..4c6f1d6b 100644 --- a/6-Data-Science-In-Wild/20-Real-World-Examples/README.md +++ b/6-Data-Science-In-Wild/20-Real-World-Examples/README.md @@ -36,6 +36,10 @@ The figure shows other domains and examples for applying data science techniques ## Data Science + Research +| ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/20-DataScience-Research.png) | +| :---------------------------------------------------------------------------------------------------------------: | +| Data Science & Research - _Sketchnote by [@nitya](https://twitter.com/nitya)_ | + While real-world applications often focus on industry use cases at scale, _research_ applications and projects can be useful from two perspectives: * _innovation opportunities_ - explore rapid prototyping of advanced concepts and testing of user experiences for next-generation applications. @@ -88,6 +92,10 @@ Using this workflow, we can explore the seasonal impacts on the sentiment of the ## Data Science + Sustainability +| ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/20-DataScience-Sustainability.png) | +| :---------------------------------------------------------------------------------------------------------------: | +| Data Science & Sustainability - _Sketchnote by [@nitya](https://twitter.com/nitya)_ | + The [2030 Agenda For Sustainable Development](https://sdgs.un.org/2030agenda) - adopted by all United Nations members in 2015 - identifies 17 goals including ones that focus on **Protecting the Planet** from degradation and the impact of climate change. The [Microsoft Sustainability](https://www.microsoft.com/en-us/sustainability) initiative supports these goals by exploring ways in which technology solutions can support and build more sustainable futures with a [focus on 4 goals](https://dev.to/azure/a-visual-guide-to-sustainable-software-engineering-53hh) - being carbon negative, water positive, zero waste, and bio-diverse by 2030. Tackling these challenges in a scalable and timely manner requires cloud-scale thinking - and large scale data. The [Planetary Computer](https://planetarycomputer.microsoft.com/) initiative provides 4 components to help data scientists and developers in this effort: diff --git a/6-Data-Science-In-Wild/README.md b/6-Data-Science-In-Wild/README.md index 1e452621..edd7a3f2 100644 --- a/6-Data-Science-In-Wild/README.md +++ b/6-Data-Science-In-Wild/README.md @@ -1,9 +1,11 @@ # Data Science in the Wild -[Brief description about the lessons in this section] +Real-world applications of data science across industries. ### Topics 1. [Data Science in the Real World](20-Real-World-Examples/README.md) ### Credits + +Written with ❤️ by [Nitya Narasimhan](https://twitter.com/nitya) diff --git a/README.md b/README.md index c754411b..0cdeaece 100644 --- a/README.md +++ b/README.md @@ -71,9 +71,9 @@ In addition, a low-stakes quiz before a class sets the intention of the student | 14 | Introduction to the Data Science lifecycle | [Lifecycle](4-Data-Science-Lifecycle/README.md) | Introduction to the data science lifecycle and its first step of acquiring and extracting data | [lesson](4-Data-Science-Lifecycle/14-Introduction/README.md) | [Jasmine](https://twitter.com/paladique) | | 15 | Analyzing | [Lifecycle](4-Data-Science-Lifecycle/README.md) | This phase of the data science lifecycle focuses on techniques to analyze data. | [lesson](4-Data-Science-Lifecycle/15-Analyzing/README.md) | [Jasmine](https://twitter.com/paladique) | | | | 16 | Communication | [Lifecycle](4-Data-Science-Lifecycle/README.md) | This phase of the data science lifecycle focuses on presenting the insights from the data in a way that makes it easier for decision makers to understand. | [lesson](4-Data-Science-Lifecycle/16-Communication/README.md) | [Jalen](https://twitter.com/JalenMcG) | | | -| 17 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/README.md) | This series of lessons introduces data science in the cloud and its benefits. | [lesson](5-Data-Science-In-Cloud/17-Introduction/README.md) | Tiffany and Maud | -| 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 and Maud | -| 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 and Maud | +| 17 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/README.md) | This series of lessons introduces data science in the cloud and its benefits. | [lesson](5-Data-Science-In-Cloud/17-Introduction/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | +| 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) | ## Offline access diff --git a/pdf/readme.pdf b/pdf/readme.pdf index 9dad2c80..3d65e4b2 100644 Binary files a/pdf/readme.pdf and b/pdf/readme.pdf differ diff --git a/sketchnotes/00-Roadmap.png b/sketchnotes/00-Roadmap.png index 7f5111e1..639ce5ee 100644 Binary files a/sketchnotes/00-Roadmap.png and b/sketchnotes/00-Roadmap.png differ diff --git a/sketchnotes/20-DataScience-Research.png b/sketchnotes/20-DataScience-Research.png new file mode 100644 index 00000000..67922cb4 Binary files /dev/null and b/sketchnotes/20-DataScience-Research.png differ diff --git a/sketchnotes/20-DataScience-Sustainability.png b/sketchnotes/20-DataScience-Sustainability.png new file mode 100644 index 00000000..af670e52 Binary files /dev/null and b/sketchnotes/20-DataScience-Sustainability.png differ