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‎README.md‎

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[Arabic](./translations/ar/README.md) | [Bengali](./translations/bn/README.md) | [Bulgarian](./translations/bg/README.md) | [Burmese (Myanmar)](./translations/my/README.md) | [Chinese (Simplified)](./translations/zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](./translations/zh-HK/README.md) | [Chinese (Traditional, Macau)](./translations/zh-MO/README.md) | [Chinese (Traditional, Taiwan)](./translations/zh-TW/README.md) | [Croatian](./translations/hr/README.md) | [Czech](./translations/cs/README.md) | [Danish](./translations/da/README.md) | [Dutch](./translations/nl/README.md) | [Estonian](./translations/et/README.md) | [Finnish](./translations/fi/README.md) | [French](./translations/fr/README.md) | [German](./translations/de/README.md) | [Greek](./translations/el/README.md) | [Hebrew](./translations/he/README.md) | [Hindi](./translations/hi/README.md) | [Hungarian](./translations/hu/README.md) | [Indonesian](./translations/id/README.md) | [Italian](./translations/it/README.md) | [Japanese](./translations/ja/README.md) | [Kannada](./translations/kn/README.md) | [Korean](./translations/ko/README.md) | [Lithuanian](./translations/lt/README.md) | [Malay](./translations/ms/README.md) | [Malayalam](./translations/ml/README.md) | [Marathi](./translations/mr/README.md) | [Nepali](./translations/ne/README.md) | [Nigerian Pidgin](./translations/pcm/README.md) | [Norwegian](./translations/no/README.md) | [Persian (Farsi)](./translations/fa/README.md) | [Polish](./translations/pl/README.md) | [Portuguese (Brazil)](./translations/pt-BR/README.md) | [Portuguese (Portugal)](./translations/pt-PT/README.md) | [Punjabi (Gurmukhi)](./translations/pa/README.md) | [Romanian](./translations/ro/README.md) | [Russian](./translations/ru/README.md) | [Serbian (Cyrillic)](./translations/sr/README.md) | [Slovak](./translations/sk/README.md) | [Slovenian](./translations/sl/README.md) | [Spanish](./translations/es/README.md) | [Swahili](./translations/sw/README.md) | [Swedish](./translations/sv/README.md) | [Tagalog (Filipino)](./translations/tl/README.md) | [Tamil](./translations/ta/README.md) | [Telugu](./translations/te/README.md) | [Thai](./translations/th/README.md) | [Turkish](./translations/tr/README.md) | [Ukrainian](./translations/uk/README.md) | [Urdu](./translations/ur/README.md) | [Vietnamese](./translations/vi/README.md)
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> **Prefer to Clone Locally?**
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>
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> This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:
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>
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> **Bash / macOS / Linux:**
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> ```bash
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> git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.git
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> cd Data-Science-For-Beginners
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> git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'
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> ```
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>
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> **CMD (Windows):**
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> ```cmd
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> git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.git
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> cd Data-Science-For-Beginners
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> git sparse-checkout set --no-cone "/*" "!translations" "!translated_images"
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> ```
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>
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> This gives you everything you need to complete the course with a much faster download.
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<!-- CO-OP TRANSLATOR LANGUAGES TABLE END -->
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‎translations/pa/.co-op-translator.json‎

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"source_file": "1-Introduction/01-defining-data-science/assignment.md",
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"language_code": "pa"
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},
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"1-Introduction/01-defining-data-science/notebook.ipynb": {
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"original_hash": "8f5eb7b3f7cc89e6d98fb32e1de65dec",
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"translation_date": "2026-02-27T09:19:18+00:00",
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"source_file": "1-Introduction/01-defining-data-science/notebook.ipynb",
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"language_code": "pa"
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},
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"1-Introduction/01-defining-data-science/solution/assignment.md": {
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"original_hash": "a8f79b9c0484c35b4f26e8aec7fc4d56",
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"translation_date": "2025-08-27T17:18:06+00:00",
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"source_file": "1-Introduction/01-defining-data-science/solution/assignment.md",
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"language_code": "pa"
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},
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"1-Introduction/01-defining-data-science/solution/notebook.ipynb": {
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"original_hash": "090bbfbfcb0c40d3d6e3236f836164ea",
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"translation_date": "2026-02-27T09:20:15+00:00",
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"source_file": "1-Introduction/01-defining-data-science/solution/notebook.ipynb",
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"language_code": "pa"
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},
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"1-Introduction/02-ethics/README.md": {
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"original_hash": "58860ce9a4b8a564003d2752f7c72851",
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"translation_date": "2025-10-03T16:23:07+00:00",
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"source_file": "2-Working-With-Data/07-python/assignment.md",
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"language_code": "pa"
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},
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"2-Working-With-Data/07-python/notebook-covidspread.ipynb": {
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"original_hash": "6335cccba01dc6ad7b15aba7a8c73f38",
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"translation_date": "2026-02-27T09:21:32+00:00",
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"source_file": "2-Working-With-Data/07-python/notebook-covidspread.ipynb",
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"language_code": "pa"
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},
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"2-Working-With-Data/08-data-preparation/README.md": {
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"original_hash": "1b560955ff39a2bcf2a049fce474a951",
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"translation_date": "2025-09-06T08:08:07+00:00",
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"language_code": "pa"
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},
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"README.md": {
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"original_hash": "9204a2806964384a56f5cb0f22bbe953",
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"translation_date": "2026-02-06T08:01:11+00:00",
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"original_hash": "f671e295a294a2559fc59d1524e001b4",
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"translation_date": "2026-02-27T09:27:19+00:00",
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"source_file": "README.md",
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"language_code": "pa"
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},

‎translations/pa/1-Introduction/01-defining-data-science/README.md‎

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[![ਡਾਟਾ ਸਾਇੰਸ ਦੀ ਪਰਿਭਾਸ਼ਾ ਵੀਡੀਓ](../../../../translated_images/pa/video-def-ds.6623ee2392ef1abf6d7faf3fad10a4163642811749da75f44e35a5bb121de15c.png)](https://youtu.be/beZ7Mb_oz9I)
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[![ਡਾਟਾ ਸਾਇੰਸ ਦੀ ਪਰਿਭਾਸ਼ਾ ਵੀਡੀਓ](../../../../translated_images/pa/video-def-ds.6623ee2392ef1abf.webp)](https://youtu.be/beZ7Mb_oz9I)
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## [ਪ੍ਰੀ-ਲੈਕਚਰ ਕਵਿਜ਼](https://ff-quizzes.netlify.app/en/ds/quiz/0)
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ਇਸ ਚੁਣੌਤੀ ਵਿੱਚ, ਅਸੀਂ ਟੈਕਸਟਾਂ ਨੂੰ ਦੇਖ ਕੇ ਡੇਟਾ ਸਾਇੰਸ ਦੇ ਖੇਤਰ ਨਾਲ ਸਬੰਧਤ ਸੰਕਲਪਾਂ ਨੂੰ ਪਤਾ ਕਰਨ ਦੀ ਕੋਸ਼ਿਸ਼ ਕਰਾਂਗੇ। ਅਸੀਂ ਡੇਟਾ ਸਾਇੰਸ 'ਤੇ ਇੱਕ ਵਿਕੀਪੀਡੀਆ ਲੇਖ ਲਵਾਂਗੇ, ਟੈਕਸਟ ਨੂੰ ਡਾਊਨਲੋਡ ਅਤੇ ਪ੍ਰੋਸੈਸ ਕਰਾਂਗੇ, ਅਤੇ ਫਿਰ ਇੱਕ ਵਰਡ ਕਲਾਉਡ ਬਣਾਵਾਂਗੇ ਜਿਵੇਂ ਕਿ ਇਹ ਹੈ:
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![ਡੇਟਾ ਸਾਇੰਸ ਲਈ ਵਰਡ ਕਲਾਉਡ](../../../../translated_images/pa/ds_wordcloud.664a7c07dca57de017c22bf0498cb40f898d48aa85b3c36a80620fea12fadd42.png)
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![ਡੇਟਾ ਸਾਇੰਸ ਲਈ ਵਰਡ ਕਲਾਉਡ](../../../../translated_images/pa/ds_wordcloud.664a7c07dca57de0.webp)
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ਕੋਡ ਨੂੰ ਪੜ੍ਹਨ ਲਈ [`notebook.ipynb`](../../../../1-Introduction/01-defining-data-science/notebook.ipynb ':ignore') 'ਤੇ ਜਾਓ। ਤੁਸੀਂ ਕੋਡ ਨੂੰ ਚਲਾ ਵੀ ਸਕਦੇ ਹੋ, ਅਤੇ ਦੇਖ ਸਕਦੇ ਹੋ ਕਿ ਇਹ ਸਾਰੇ ਡੇਟਾ ਰੂਪਾਂਤਰਨਾਂ ਨੂੰ ਅਸਲ ਸਮੇਂ ਵਿੱਚ ਕਿਵੇਂ ਕਰਦਾ ਹੈ।
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