Hello, 07-380

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    <td>Course number</td> <td>07-380</td>
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    <td>Long Title</td> <td>Artificial Intelligence and Machine Learning II
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    <td>Short Title</td> <td>AI & ML II
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    <td>Description</td> <td>07-380 is the second in a two-course sequence covering the breadth and depth of AI/ML required by the AI major/minor. Building upon 07-280 AI & ML I, 07-380 is designed to both solidify the fundamental components of AI and ML as well as introduce students to the latest breakthroughs in the rapidly changing AI landscape.
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    <td>Key Topics</td> <td>AI ethics, ML theory, game theory, unsupervised learning, ensemble learning, recommender systems, convex and non-convex optimization, probabilistic graphical models, automated theorem proving, planning, distributed deep learning, generative AI, reinforcement learning with human feedback, vision transformers, diffusion models, variational autoencoders
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    <td>Prerequisite Knowledge</td> <td>The prequisites for this course are: 07-280 AI & ML I, 21-122 Integration and Approximation, and (36-225 Introduction to Probability Theory or 36-235 Probability and Statistical Inference I or 15-259 Probability and Computing) 
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    <td>Course Relevance</td> <td>07-380 follows 07-280 AI & ML I as the second in a two-course sequence covering the breadth and depth of AI/ML required by the AI major/minor.
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    <td>Assessment Structure</td> <td>Assessment includes quizzes/exams, homework assignments (including written and programming portions), and course project(s).
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    <td>Learning Resources</td> <td>Online readings. Recitations focused on preparing students for homework assignments. Online discussion forum. Office hours.
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    <td>Extra Time Commitments</td> <td>Potentially evening quizzes/exams</td>
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