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Revised NUPath Writeup — CS6140
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A. Demonstrate facility with the writing conventions of genres in the academic field or profession.

The course requires students to communicate technical work using the conventions standard to machine learning research and professional practice. Across assignments and the course project, students are expected to articulate problem formulations, describe datasets and experimental designs, justify modeling and algorithmic decisions, and present empirical results using established norms. Written submissions emphasize precision, reproducibility, and clarity, including explicit documentation of implementation details, evaluation metrics, and experimental protocols. Through this work, students practice presenting technical findings in a style consistent with professional research reports in machine learning.

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B. Identify credible, relevant sources and engage and cite them appropriately in their written work.

Students are expected to ground their technical work in established sources from the machine learning literature. Course assignments require students to implement and analyze algorithms or techniques drawn from research papers, textbooks, or authoritative technical references, with clear attribution to the original sources. Students engage with these sources by explaining how prior work informs their implementation choices and experimental design. In the course project, students situate their work within existing research by identifying relevant foundational and related studies and by distinguishing prior contributions from their own. Citations are documented using standard conventions common to major machine learning conferences and journals.

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C. Draft, revise, and edit their writing using feedback from readers.

The course emphasizes iterative improvement of technical work through structured feedback. In assignments, students receive feedback on code implementations and accompanying technical documentation, including issues of correctness, organization, clarity, and adherence to specified requirements, and are expected to revise their work accordingly. For the course project, students develop written materials over multiple stages, incorporating feedback on technical accuracy, structure, and clarity of exposition. This process reflects the iterative development and review practices typical of research and professional technical work.