DS 121 A: Foundations of Data Science II

We will use Python as the language for teaching and for
assignments that require coding.

Instructions for installing and using Python can be found here: https://piazza.com/class_profile/get_resource/m0lemb6fw34578/m0lf9g2amjw6ch (also available in the Piazza Resources tab).

Completed homework assignments must be submitted via Gradescope at https://www.gradescope.com/courses/852516

Graded exams and discussion lab worksheets will be returned to you via Gradescope as well.

You must read and adhere to BU’s Academic Code of Conduct, which is available here: https://www.bu.edu/academics/policies/academic-conduct-code/

Please familiarize yourself with this code, its definitions of misconduct and plagiarism, and its sanctions. Violations of this code will result in receiving a score of 0 on the homework or exam, and may be grounds for referral to BU’s Academic Conduct Committee. If you have any questions about the policy, you must ask me in person or via private Piazza note before taking an action that might be a violation.

For homeworks: the goal of homework assignments is to learn. Hence, I encourage you to use any and all resources that can help you learn the material: computers/calculators, Piazza, lecture notes, textbooks, other websites, and your fellow classmates. There are only a few rules to keep in mind.

- You cannot copy solutions from anyone else, or give your solutions to a classmate to copy.
- You also cannot actively search for the solutions to the homework questions on the Internet or in any other source.
- Your submission must list (a) names of all classmates you worked with, (b) all websites you used besides the ones listed in the lecture notes or textbooks, and (c) all code that you used from other sources, including the exact prompts and responses from any AI tool.

Taking ideas without attribution will be considered plagiarism.

For exams: the goal of the exams is for you to show me what you have learned, so any form of collaboration is strictly prohibited. Computers and notes are also forbidden during exams unless I explicitly state otherwise. That said, I encourage you to collaborate with classmates when studying lecture materials and preparing for the exams.

All written work in this course must be original to you. If you consult outside texts, or other forms of assistance, cite these sources in the proper format—at a minimum, include the author, title, and website link for all external sources (books, journals, lectures, web sites, AI). We are required to report all suspected cases of plagiarism to the Academic Dean for review.

Academic integrity in computing coursework has some special aspects. Please review the examples of plagiarism as provided by the BU Computer Science department: https://www.bu.edu/cs/undergraduate/undergraduate-life/academic-integrity/.

All submitted work in this course must conform to the CDS Generative AI Assistance Policy, which you can read at https://www.bu.edu/cds-faculty/culture-community/gaia-policy/. Also, keep in mind that AI tools are often wrong!

Even if an AI tool is correct, it can be difficult to make sure you're taking advantage of it to enhance rather than substitute for your own learning experience. Here is a student response from last year's course evaluation: "Don't try to use Chat GPT or other NLP tools for your assignments, as they may crunch your time spent, but hinder your understanding of the material."