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Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
Johns Hopkins University 3 credits Computer Science
The rise of massive self-supervised (pre-trained) models has transformed various data-driven fields such as natural language processing, computer vision, robotics, and medical imaging. This advanced graduate course aims to provide a holistic view of the issues related to these models: We will start with the history of how we got here, and then delve into the latest success stories. We will then focus on the implications of these technologies: social harms, security risks, legal issues, and environmental impacts. The class ends with reflections on the future implications of this trajectory.Required Course Background: knowledge equivalent to EN.601.471/671 or EN.601.465/665; linear algebra and statistics. Prerequisite(s): EN.601.471 OR EN.601.671 OR EN.601.465 OR EN.601.665
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Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
Learn how to choose a research topic you can actually research. Discover how to narrow broad ideas, find reliable sources, and develop a focused research question.
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