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dataset-metadata.json
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"datasetSlugNullable": "learning-path-index-dataset",
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"subtitleNullable": "A comprehensive dataset of Data Science, ML and AI learning paths and courses",
"descriptionNullable": "# Description\nThe **Learning Path Index Dataset** is a comprehensive collection of byte-sized courses and learning materials tailored for individuals eager to delve into the fields of Data Science, Machine Learning, and Artificial Intelligence (AI), making it an indispensable reference for students, professionals, and educators in the Data Science and AI communities.\n\nThis **Kaggle Dataset** along with the KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index) were created by the mentors and mentees of **Cohort 3** [KaggleX BIPOC Mentorship Program](https://www.kaggle.com/kagglex) (between _August 2023_ and _November 2023_, also [see this](https://www.kaggle.com/discussions/general/409607)). See **Credits** section at the bottom of the long description.\n\n# Inspiration\nThis dataset was created out of a commitment to facilitate learning and growth within the Data Science, Machine Learning, and AI communities. It started off as an idea at the end of **Cohort 2** of the [KaggleX BIPOC Mentorship Program](https://www.kaggle.com/kagglex) brainstorming and feedback session. It was one of the ideas to create byte-sized learning material to help our KaggleX mentees learn things faster. It aspires to simplify the process of finding, evaluating, and selecting the most fitting educational resources.\n\n# Context\nThis dataset was meticulously curated to assist learners in navigating the vast landscape of Data Science, Machine Learning, and AI education. It serves as a compass for those aiming to develop their skills and expertise in these rapidly evolving fields. \n\nThe mentors and mentees communicated via **Discord**, **Trello**, **Google Hangout**, etc... to put together these artifacts and made them public for everyone to _use and contribute back_.\n\n# Sources\nThe dataset compiles data from a curated selection of reputable sources including leading educational platforms such as **Google Developer, Google Cloud Skill Boost, IBM, Fast AI**, etc. By drawing from these trusted sources, we ensure that the data is both accurate and pertinent. The raw data and other artifacts as a result of this exercise can be found on the GitHub Repo i.e. KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index).\n\n# Content\nThe dataset encompasses the following attributes:\n\n- **Course / Learning Material:** The title of the Data Science, Machine Learning, or AI course or learning material.\n- **Source:** The provider or institution offering the course.\n- **Course Level:** The proficiency level, ranging from Beginner to Advanced.\n- **Type (Free or Paid):** Indicates whether the course is available for free or requires payment.\n- **Module:** Specific module or section within the course.\n- **Duration:** The estimated time required to complete the module or course.\n- **Module / Sub-module Difficulty Level:** The complexity level of the module or sub-module.\n- **Keywords / Tags / Skills / Interests / Categories:** Relevant keywords, tags, or categories associated with the course with a focus on Data Science, Machine Learning, and AI.\n- **Links:** Hyperlinks to access the course or learning material directly.\n\n# How to contribute to this initiative?\n\n- You can also join us by taking part in the next [KaggleX BIPOC Mentorship program](https://www.kaggle.com/kagglex) (also [see this](https://www.kaggle.com/discussions/general/409607))\n- Keep your eyes open on the **Kaggle Discussions** page and other **KaggleX** social media channels. Or find us on the [Kaggle Discord](https://www.kaggle.com/discussions/general/429933) channel to learn more about the next steps\n- Create notebooks from this data\n- Create supplementary or complementary data for or from this dataset\n- Submit corrections/enhancements or anything else to help improve this dataset so it has a wider use and purpose\n\n# License\nThe **Learning Path Index Dataset** is openly shared under a permissive license, allowing users to utilize the data for educational, analytical, and research purposes within the Data Science, Machine Learning, and AI domains. Feel free to _fork the dataset_ and make it your own, we would be delighted if you contributed back to the dataset and/or our KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index) as well.\n\n# Important Links\n\n- [KaggleX BIPOC Mentorship program](https://www.kaggle.com/kagglex) (also [see this](https://www.kaggle.com/discussions/general/409607))\n- KaggleX [Learning Path Index Dataset](https://www.kaggle.com/datasets/neomatrix369/learning-path-index-dataset)\n- KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index)\n- [New Official Kaggle Discord Server!](https://www.kaggle.com/discussions/general/429933)\n\n# Credits\nCredits for all the work done to create this Kaggle Dataset and the KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index) goes to these mentors and mentees (in no particular order): [Manish Kumar](https://www.kaggle.com/manishkr1754), [Ben Aji](https://www.kaggle.com/benajii) (_mentor_), [Emmanuel Katchy](https://www.kaggle.com/tobetek), [Ezeogu Ernest](https://www.kaggle.com/tobetek), [Manish](https://www.kaggle.com/manish5), [Mustafa](https://www.kaggle.com/mustafa254), [Nnamdi Idowu-Anifowoshe](https://www.kaggle.com/idowuchukwudi), [Sheba Alkali](https://www.kaggle.com/shebaalkali), [Zainab ikeoluwa](https://www.kaggle.com/zainabikeoluwa), [Wendy Mak](https://www.kaggle.com/wwymak) (_mentor_), [Misirya Hameed](https://www.linkedin.com/in/misiriya-shahul-hameed-b3957875) (_mentor_), [Chukwuebuka Obi](https://www.kaggle.com/chukwuebukaobi), [Victor Umunna](https://www.kaggle.com/victorumunna), [Pui Yueng](https://www.kaggle.com/lorentzyeung), [Afolake Solomon](https://www.kaggle.com/flakkyddon), [Faith Osoro](https://www.kaggle.com/faithosoro), [Chukwudi Idowu](https://www.kaggle.com/chukwudiidowu), and many others who were part of the **Cohort 3** [KaggleX BIPOC Mentorship Program](https://www.kaggle.com/kagglex) (between _August 2023_ and _November 2023_, also [see this](https://www.kaggle.com/discussions/general/409607)).\n\nOur gratitude also goes to our silent supporters of this initiative from organisers to the mentors and mentees whose help and support kept us going.\n\n_**Note:** In case your name or mention is missed out in the above list, then please let us know._",
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"description": "# Description\nThe **Learning Path Index Dataset** is a comprehensive collection of byte-sized courses and learning materials tailored for individuals eager to delve into the fields of Data Science, Machine Learning, and Artificial Intelligence (AI), making it an indispensable reference for students, professionals, and educators in the Data Science and AI communities.\n\nThis **Kaggle Dataset** along with the KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index) were created by the mentors and mentees of **Cohort 3** [KaggleX BIPOC Mentorship Program](https://www.kaggle.com/kagglex) (between _August 2023_ and _November 2023_, also [see this](https://www.kaggle.com/discussions/general/409607)). See **Credits** section at the bottom of the long description.\n\n# Inspiration\nThis dataset was created out of a commitment to facilitate learning and growth within the Data Science, Machine Learning, and AI communities. It started off as an idea at the end of **Cohort 2** of the [KaggleX BIPOC Mentorship Program](https://www.kaggle.com/kagglex) brainstorming and feedback session. It was one of the ideas to create byte-sized learning material to help our KaggleX mentees learn things faster. It aspires to simplify the process of finding, evaluating, and selecting the most fitting educational resources.\n\n# Context\nThis dataset was meticulously curated to assist learners in navigating the vast landscape of Data Science, Machine Learning, and AI education. It serves as a compass for those aiming to develop their skills and expertise in these rapidly evolving fields. \n\nThe mentors and mentees communicated via **Discord**, **Trello**, **Google Hangout**, etc... to put together these artifacts and made them public for everyone to _use and contribute back_.\n\n# Sources\nThe dataset compiles data from a curated selection of reputable sources including leading educational platforms such as **Google Developer, Google Cloud Skill Boost, IBM, Fast AI**, etc. By drawing from these trusted sources, we ensure that the data is both accurate and pertinent. The raw data and other artifacts as a result of this exercise can be found on the GitHub Repo i.e. KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index).\n\n# Content\nThe dataset encompasses the following attributes:\n\n- **Course / Learning Material:** The title of the Data Science, Machine Learning, or AI course or learning material.\n- **Source:** The provider or institution offering the course.\n- **Course Level:** The proficiency level, ranging from Beginner to Advanced.\n- **Type (Free or Paid):** Indicates whether the course is available for free or requires payment.\n- **Module:** Specific module or section within the course.\n- **Duration:** The estimated time required to complete the module or course.\n- **Module / Sub-module Difficulty Level:** The complexity level of the module or sub-module.\n- **Keywords / Tags / Skills / Interests / Categories:** Relevant keywords, tags, or categories associated with the course with a focus on Data Science, Machine Learning, and AI.\n- **Links:** Hyperlinks to access the course or learning material directly.\n\n# How to contribute to this initiative?\n\n- You can also join us by taking part in the next [KaggleX BIPOC Mentorship program](https://www.kaggle.com/kagglex) (also [see this](https://www.kaggle.com/discussions/general/409607))\n- Keep your eyes open on the **Kaggle Discussions** page and other **KaggleX** social media channels. Or find us on the [Kaggle Discord](https://www.kaggle.com/discussions/general/429933) channel to learn more about the next steps\n- Create notebooks from this data\n- Create supplementary or complementary data for or from this dataset\n- Submit corrections/enhancements or anything else to help improve this dataset so it has a wider use and purpose\n\n# License\nThe **Learning Path Index Dataset** is openly shared under a permissive license, allowing users to utilize the data for educational, analytical, and research purposes within the Data Science, Machine Learning, and AI domains. Feel free to _fork the dataset_ and make it your own, we would be delighted if you contributed back to the dataset and/or our KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index) as well.\n\n# Important Links\n\n- [KaggleX BIPOC Mentorship program](https://www.kaggle.com/kagglex) (also [see this](https://www.kaggle.com/discussions/general/409607))\n- KaggleX [Learning Path Index Dataset](https://www.kaggle.com/datasets/neomatrix369/learning-path-index-dataset)\n- KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index)\n- [New Official Kaggle Discord Server!](https://www.kaggle.com/discussions/general/429933)\n\n# Credits\nCredits for all the work done to create this Kaggle Dataset and the KaggleX [Learning Path Index GitHub Repo](https://github.com/neomatrix369/learning-path-index) goes to these mentors and mentees (in no particular order): [Manish Kumar](https://www.kaggle.com/manishkr1754), [Ben Aji](https://www.kaggle.com/benajii) (_mentor_), [Emmanuel Katchy](https://www.kaggle.com/tobetek), [Ezeogu Ernest](https://www.kaggle.com/tobetek), [Manish](https://www.kaggle.com/manish5), [Mustafa](https://www.kaggle.com/mustafa254), [Nnamdi Idowu-Anifowoshe](https://www.kaggle.com/idowuchukwudi), [Sheba Alkali](https://www.kaggle.com/shebaalkali), [Zainab ikeoluwa](https://www.kaggle.com/zainabikeoluwa), [Wendy Mak](https://www.kaggle.com/wwymak) (_mentor_), [Misirya Hameed](https://www.linkedin.com/in/misiriya-shahul-hameed-b3957875) (_mentor_), [Chukwuebuka Obi](https://www.kaggle.com/chukwuebukaobi), [Victor Umunna](https://www.kaggle.com/victorumunna), [Pui Yueng](https://www.kaggle.com/lorentzyeung), [Afolake Solomon](https://www.kaggle.com/flakkyddon), [Faith Osoro](https://www.kaggle.com/faithosoro), [Chukwudi Idowu](https://www.kaggle.com/chukwudiidowu), and many others who were part of the **Cohort 3** [KaggleX BIPOC Mentorship Program](https://www.kaggle.com/kagglex) (between _August 2023_ and _November 2023_, also [see this](https://www.kaggle.com/discussions/general/409607)).\n\nOur gratitude also goes to our silent supporters of this initiative from organisers to the mentors and mentees whose help and support kept us going.\n\n_**Note:** In case your name or mention is missed out in the above list, then please let us know._",
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