At DeepLearning.AI, we emphasize the quality of our curriculum. We want members of our online community to join us in maintaining the integrity of our online courses, respecting our instructors’ contributions, and protecting the value of earning a certificate. We expect all community members to comply with both Coursera’s Honor Code as well as our own honor code, described below.
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Plagiarism is when you take someone else’s work or ideas and pass them off as your own without giving credit to the original owner. This is a serious academic offense. If we find that you plagiarize any material, you will be removed from our community forum as well as any courses you are enrolled in. Any certificates you hold from DeepLearning.AI will be revoked. No refunds will be given to learners who plagiarize.
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You should not post anything digital that belongs to someone else without permission or citing the work. You should not post descriptions of, links to, or methods for stealing someone’s intellectual property (software, video, audio, images).
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You should not post descriptions of, links to, or methods for breaking any laws.
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Only share data for legitimate purposes.
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You may not share code repositories, websites, streaming or any links that lead to data that belongs to DeepLearning.AI (Such as quizzes, lectures, and labs). If you are sharing some code used for projects, you must cite DeepLearning.AI.
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You should not share complete code or your solutions to quizzes or programming assignments with anyone other than a DeepLearning.AI mentor or staff member. If you are found posting solutions to our community forum, Github, or any other code repository, DeepLearning.AI reserves the right to suspend your account and conduct a full review of your engagement with our community. This may result in your being expelled from the community and having your certificates revoked.
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You should not distribute slides, lecture notes, or other course materials from our DeepLearning.AI courses for commercial purposes. For example, you should not include notes on Github in exchange for any form of payment or service. This includes the sharing of code, solutions to quizzes or programming assignments to external groups/organizations.
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Soliciting other forum members to join other communities or purchase outside products is prohibited.
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You may freely distribute lecture slides for educational purposes under the Creative Commons License, as long as you cite DeepLearning.AI as the source. For example: DeepLearning.AI (2021, October 25). What is AI? Retrieved from AI4E: Lecture Notes
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Obtain consent before sharing data. If you are sharing data that has been collected from individuals, you must obtain their consent before doing so.
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Be clear about the terms of use for the data you are sharing. Let others know how they can use the data, and what restrictions there are (if any).
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Be mindful of the potential biases in the data you are sharing. Data can reflect the biases of the people who collected it and the systems that were used to collect it. Be transparent about any potential biases in the data, and help others to understand how these biases might affect their use of the data.
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Cite the authors of any data you share. This can be done by including a reference to the original publication or website where you found the data.
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If you are unsure of how to cite the authors of a particular dataset, please consult with a community moderator or other knowledgeable member of the community.
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Do not share data that is not your own without the permission of the copyright holder.
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If you are unsure whether or not you have permission to share a particular dataset, please err on the side of caution and do not share it.
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Be respectful of the authors of the data you share. This means not altering the data in any way without their permission and not using the data in a way that is inconsistent with their stated intentions.
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If you are unsure of how to cite a dataset in a particular style, please ask members of the community.
By following these guidelines, you can help to ensure that the authors of the data you share are properly credited for their work. This is important for both ethical and legal reasons.
If you see someone violating this code of conduct, please report it to the community moderators. We will take all reports seriously and take appropriate action.