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4 changes: 2 additions & 2 deletions 1-Introduction/01-defining-data-science/README.md
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[![Defining Data Science Video](images/video-def-ds.png)](https://youtu.be/beZ7Mb_oz9I)

## [Pre-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/0)
## [Pre-lecture quiz](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/0)

## What is Data?
In our everyday life, we are constantly surrounded by data. The text you are reading now is data. The list of phone numbers of your friends in your smartphone is data, as well as the current time displayed on your watch. As human beings, we naturally operate with data by counting the money we have or by writing letters to our friends.
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## [Post-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/1)
## [Post-lecture quiz](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/1)

## Assignments

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[![Video definiendo la ciencia de datos](../images/video-def-ds.png)](https://youtu.be/beZ7Mb_oz9I)

## [Cuestionario antes de la lección](https://red-water-0103e7a0f.azurestaticapps.net/quiz/0)
## [Cuestionario antes de la lección](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/0)

## ¿Qué son los datos?
En nuestra vida cotidiana estamos rodeados de datos. El texto que estás leyendo ahora mismo son datos. La lista de tus contactos en tu teléfono móvil son datos, como lo es la hora que muestra tu reloj. Como seres humanos, operamos naturalmente condatos como por ejemplo contando el dinero que tenemos o escribiendo cartas a nuestros amigos.
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## [Cuestionario después de la lección](https://red-water-0103e7a0f.azurestaticapps.net/quiz/1)
## [Cuestionario después de la lección](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/1)

## Tareas

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[![डेटा विज्ञान वीडियो को परिभाषित करना](/1-Introduction/01-defining-data-science/images/video-def-ds.png)](https://youtu.be/beZ7Mb_oz9I)

## [प्री-लेक्चर क्विज](https://red-water-0103e7a0f.azurestaticapps.net/quiz/0)
## [प्री-लेक्चर क्विज](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/0)

## डेटा क्या है?
अपने दैनिक जीवन में हम लगातार डेटा से घिरे रहते हैं। अभी आप जो पाठ पढ़ रहे हैं वह डेटा है। आपके स्मार्टफ़ोन में आपके मित्रों के फ़ोन नंबरों की सूची डेटा है, साथ ही आपकी घड़ी पर प्रदर्शित वर्तमान समय भी है। मनुष्य के रूप में, हम स्वाभाविक रूप से हमारे पास मौजूद धन की गणना करके या अपने मित्रों को पत्र लिखकर डेटा के साथ काम करते हैं।
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## [व्याख्यान के बाद प्रश्नोत्तरी](https://red-water-0103e7a0f.azurestaticapps.net/quiz/1)
## [व्याख्यान के बाद प्रश्नोत्तरी](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/1)

## कार्य (Assignments)

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[![데이터 과학(Data Science) 정의 영상](../images/video-def-ds.png)](https://youtu.be/pqqsm5reGvs)

## [Pre-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/0)
## [Pre-lecture quiz](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/0)

## 데이터란 무엇인가?
일상 생활에서 우리는 항상 데이터에 둘러싸여 있습니다. 지금 당신이 읽고 있는 이 글, 당신의 스마트폰 안에 있는 친구들의 전화번호 목록도 데이터이며, 시계에 표시되는 현재 시간 역시 마찬가지입니다. 인간으로서 우리는 가지고 있는 돈을 세거나 친구들에게 편지를 쓰면서 자연스럽게 데이터를 조작합니다.
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## [강의 후 퀴즈](https://red-water-0103e7a0f.azurestaticapps.net/quiz/1)
## [강의 후 퀴즈](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/1)

## 과제

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[![Defining Data Science Video](../images/video-def-ds.png)](https://youtu.be/beZ7Mb_oz9I)

## [Starttoets data science](https://red-water-0103e7a0f.azurestaticapps.net/quiz/0)
## [Starttoets data science](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/0)

## Wat is Data?
In ons dagelijks leven zijn we voortdurend omringd door data. De tekst die je nu leest is data. De lijst met telefoonnummers van je vrienden op je smartphone is data, evenals de huidige tijd die op je horloge wordt weergegeven. Als mens werken we van nature met data, denk aan het geld dat we moeten tellen of door berichten te schrijven aan onze vrienden.
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> Als je niet weet hoe je code in een Jupyter Notebook moet uitvoeren, kijk dan eens naar [dit artikel](https://soshnikov.com/education/how-to-execute-notebooks-from-github/).
## [Post-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/1)
## [Post-lecture quiz](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/1)

## Opdrachten

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[![Definindo Ciências de Dados](../images/video-def-ds.png)](https://youtu.be/pqqsm5reGvs)

## [Quiz pré-aula](https://red-water-0103e7a0f.azurestaticapps.net/quiz/0)
## [Quiz pré-aula](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/0)

## O que são Dados?
Na nossa vida cotidiana, nós estamos constantemente cercados por dados. O texto que você está lendo agora é um dado, a lista de telefones dos seus amigos no seu celular é um dado, assim como o horário atual mostrado no seu relógio. Como seres humanos, nós operamos naturalmente com dados. contando o dinheiro que temos ou escrevendo cartas para os nossos amigos.
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## [Quiz pós-aula](https://red-water-0103e7a0f.azurestaticapps.net/quiz/1)
## [Quiz pós-aula](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/1)

## Tarefas

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[![Defining Data Science Video](../images/video-def-ds.png)](https://youtu.be/beZ7Mb_oz9I)

## [Вступительный тест](https://red-water-0103e7a0f.azurestaticapps.net/quiz/0)
## [Вступительный тест](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/0)

## Что такое данные?
В повседневной жизни мы окружены данными. Текст, который Вы в данный момент читаете, является данными, список номеров телефонов друзей в Вашем смартфоне является данными, также как и время на Ваших часах. Люди умеют оперировать даными естественным образом, считая деньги, которые у нас есть, или составляя письма нашим друзьям.
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> Если Вы не знаете, как запустить код в Jupyter Notebook, прочтите [данную статью](https://soshnikov.com/education/how-to-execute-notebooks-from-github/).

## [Проверочный тест](https://red-water-0103e7a0f.azurestaticapps.net/quiz/1)
## [Проверочный тест](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/1)

## Домашнее задание

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## [Pre-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/2) 🎯
## [Pre-lecture quiz](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/2) 🎯

## Basic Definitions

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The latter requires [collaborative approaches to defining ethics cultures](https://towardsdatascience.com/why-ai-ethics-requires-a-culture-driven-approach-26f451afa29f) that build emotional connections and consistent shared values _across organizations_ in the industry. This calls for more [formalized data ethics cultures](https://www.codeforamerica.org/news/formalizing-an-ethical-data-culture/) in organizations - allowing _anyone_ to [pull the Andon cord](https://en.wikipedia.org/wiki/Andon_(manufacturing)) (to raise ethics concerns early in the process) and making _ethical assessments_ (e.g., in hiring) a core criteria team formation in AI projects.

---
## [Post-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/3) 🎯
## [Post-lecture quiz](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/3) 🎯
## Review & Self Study

Courses and books help with understanding core ethics concepts and challenges, while case studies and tools help with applied ethics practices in real-world contexts. Here are a few resources to start with.
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इस पाठ में, हम डेटा नैतिकता के आकर्षक क्षेत्र के बारे में सीखेंगे - मूल अवधारणाओं और चुनौतियों से लेकर केस-स्टडी और शासन जैसी एप्लाइड AI अवधारणाओं तक - जो डेटा और AI के साथ काम करने वाली समूह और संगठनों में नैतिकता संस्कृति स्थापित करने में मदद करते हैं ।

## [पाठ से पहले की प्रश्नोत्तरी](https://red-water-0103e7a0f.azurestaticapps.net/quiz/2) 🎯
## [पाठ से पहले की प्रश्नोत्तरी](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/2) 🎯

## मूल परिभाषाएं

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बाद वाले को [नैतिक संस्कृतियों को परिभाषित करने के लिए सहयोगात्मक दृष्टिकोण](https://towardsdatascience.com/why-ai-ethics-requires-a-culture-drive-approach-26f451afa29f) की आवश्यकता होती है, जो पूरे संगठनों में भावनात्मक संबंध और सुसंगत साझा मूल्यों का निर्माण करते हैं । यह संगठनों में अधिक [औपचारिक डेटा नैतिकता संस्कृतियों](https://www.codeforamerica.org/news/formalizing-an-ethical-data-culture/) की मांग करता है - _किसी_ को [एंडोन कॉर्ड को खींचने](https://en.wikipedia.org/wiki/Andon_(manufacturing)) की अनुमति देता है (इस प्रक्रिया में नैतिकता संबंधी चिंताओं को जल्दी उठाने के लिए) और एआई परियोजनाओं में _नैतिक मूल्यांकन_ (उदाहरण के लिए, भर्ती में) एक मुख्य मानदंड टीम गठन करना ।

---
## [व्याख्यान के बाद प्रश्नोत्तरी](https://red-water-0103e7a0f.azurestaticapps.net/quiz/3) 🎯
## [व्याख्यान के बाद प्रश्नोत्तरी](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/3) 🎯
## समीक्षा और स्व अध्ययन

पाठ्यक्रम और पुस्तकें मूल नैतिकता अवधारणाओं और चुनौतियों को समझने में मदद करती हैं, जबकि केस स्टडी और उपकरण वास्तविक दुनिया के संदर्भों में लागू नैतिकता प्रथाओं के साथ मदद करते हैं। शुरू करने के लिए यहां कुछ संसाधन दिए गए हैं।
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## [강의 전 퀴즈](https://red-water-0103e7a0f.azurestaticapps.net/quiz/2) 🎯
## [강의 전 퀴즈](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/2) 🎯

## 기본 정의

Expand Down Expand Up @@ -247,7 +247,7 @@ _준수_ ("법규"를 충족하기 위해 충분히 노력함)와 (골화, 정
후자는 산업에서 _조직 전체적으로_ 정서적 연결과 일관된 공유 가치를 구축하는 [윤리 문화를 정의하기 위한 협력적 접근 방식](https://towardsdatascience.com/why-ai-ethics-requires-a-culture-driven-approach-26f451afa29f)이 필요합니다. 이것은 조직에서 더 많은 [공식화된 데이터 윤리 문화](https://www.codeforamerica.org/news/formalizing-an-ethical-data-culture/)를 요구합니다. 이런 문화는 _누구나_ (프로세스 초기에 윤리 문제 제기를 위해) [Andon 강령을 사용하고](https://en.wikipedia.org/wiki/Andon_(manufacturing)) _윤리적 평가_ (예: 고용 시)를 AI 프로젝트의 핵심 기준 팀 구성으로 만듭니다.

---
## [강의 후 퀴즈](https://red-water-0103e7a0f.azurestaticapps.net/quiz/3) 🎯
## [강의 후 퀴즈](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/3) 🎯
## 복습 & 독학

과정과 책은 핵심 윤리 개념과 과제를 이해하는 데 도움이 되며, Case Study와 도구는 실제 상황에서 윤리 사항들을 적용하는 데 도움이 됩니다. 다음은 시작을 할 때 도움이 되는 몇가지 자료들입니다.
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## [Pre-college quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/2) 🎯
## [Pre-college quiz](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/2) 🎯

## Basisdefinities

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Dit laatste vereist [samenwerkingsbenaderingen voor het definiëren van ethische culturen](https://towardsdatascience.com/why-ai-ethics-requires-a-culture-driven-approach-26f451afa29f) die emotionele verbindingen en consistente gedeelde waarden _over organisaties_ in de industrie. Dit vraagt ​​om meer [geformaliseerde data-ethiekculturen](https://www.codeforamerica.org/news/formalizing-an-ethical-data-culture/) in organisaties - waardoor _iedereen_ [aan het Andon-koord kan trekken](https:/ /en.wikipedia.org/wiki/Andon_(manufacturing)) (om ethische problemen vroeg in het proces aan de orde te stellen) en het maken van _ethische beoordelingen_ (bijvoorbeeld bij het aannemen) een kerncriterium voor teamvorming in AI-projecten.

---
## [Quiz voor na het college](https://red-water-0103e7a0f.azurestaticapps.net/quiz/3) 🎯
## [Quiz voor na het college](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/3) 🎯
## Review & Zelfstudie

Cursussen en boeken helpen bij het begrijpen van kernconcepten en uitdagingen op het gebied van ethiek, terwijl casestudy's en hulpmiddelen helpen bij toegepaste ethische praktijken in echte contexten. Hier zijn een paar bronnen om mee te beginnen.
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## [Quiz pré aula](https://red-water-0103e7a0f.azurestaticapps.net/quiz/2) 🎯
## [Quiz pré aula](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/2) 🎯

## Definição Básica

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Este último requere [abordagens colaborativas para definir culturas éticas](https://towardsdatascience.com/why-ai-ethics-requires-a-culture-driven-approach-26f451afa29f) que constrói conexões emocionais e valores compartilhados consistentes _em todas as organizações_ na indústria. Isso requere mais [culturas de ética de dados formalizadas](https://www.codeforamerica.org/news/formalizing-an-ethical-data-culture/) nas organizações - permitindo _qualquer um_ a [puxar o cordão Andom](https://en.wikipedia.org/wiki/Andon_(manufacturing)) (para aumentar as preocupações éticas mais cedo no processo) e fazendo _avaliações éticas_ (ex. na contratação) um critério fundamental na formação de times em projetos de IA.

---
## [Quiz pós aula](https://red-water-0103e7a0f.azurestaticapps.net/quiz/3) 🎯
## [Quiz pós aula](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/3) 🎯
## Revisão e Autoestudo

Cursos e livros ajudam a entender os conceitos essencias da ética, enquanto estudos de caso e ferramentas ajudam com práticas da ética aplicado em contextos do mundo real. Aqui estão alguns recursos para começar.
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## [Вступительный тест](https://red-water-0103e7a0f.azurestaticapps.net/quiz/2) 🎯
## [Вступительный тест](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/2) 🎯

## Основные определения

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Решение этой проблемы кроется в [совместных подходах к определению этичных культур](https://towardsdatascience.com/why-ai-ethics-requires-a-culture-driven-approach-26f451afa29f), которые выстраивают эмоциональные связи и постоянные общие ценности _во всех организациях_ отрасли. Это требует более глубокой [формализации культуры в области этики данных](https://www.codeforamerica.org/news/formalizing-an-ethical-data-culture/) в организациях, позволяющей _любому_ [потянуть за ниточки](https://en.wikipedia.org/wiki/Andon_(manufacturing)) (чтобы поднять вопрос этики на ранней стадии) и провести _оценку этичности_ (например, при найме на работу) основных критериев формирования команд в проектах с ИИ.

---
## [Проверочный тест](https://red-water-0103e7a0f.azurestaticapps.net/quiz/3) 🎯
## [Проверочный тест](https://red-bay-0a991ec0f.1.azurestaticapps.net/quiz/3) 🎯
## Дополнительные источники

Курсы и книги помогут Вам понять основные этические принципы и вызовы, а примеры из реальной практики помогут с прикладными вопросами этики в контексте реального мира. Вот некоторые ресурсы, с которых можно начать:
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