- Cogs 185 ucsd how to#
- Cogs 185 ucsd pdf#
Your team may resubmit as many times as you like before the deadline. Cogs 185 ucsd pdf#
One PDF submission per group (ensure all your names and PIDs are on the PDF).One report submitted through Gradescope per group.It’s a culmination of what you learned from the assignments and lectures. The final project is a two-part report on how you would handle a complicated data science project. No late assignments accepted after 48 hours.Late assignments have 5 points deducted within the first 24 hours, and an additional 5 points during the following 24 hours.You may resubmit as many times as you like before the deadline.One PDF submission per student (ensure your name and PID are on the PDF).
You do not have edit access to the version that is linked, only the ability to copy it.
Use the Google Doc template link (found on this website under assignments), make a copy of the template. Three individual assignments submitted through Gradescope. AssignmentsĪssignments will focus on applying the concepts covered in lectures and readings. To see what topics will be introduced in this course, see the side nav menu and click on topics. This course will introduce you to the broad topics in data science, discuss what it means to be a data scientist, and get you on your way to thinking like a data scientist. This class is a survey course intended to get you all excited about becoming data scientists! Data are everywhere and they’re being used in tried-and-true, new, and creative ways. Readings as well as lecture material will be reviewed in the section and it is to your benefit to go and ask questions. Section attendance is not mandatory, however, groups will be created within sections (usually week 2). These will be made available to you (UCSD podcast). However, lecture attendance is not required. Our goal is to make lectures and office hours worth your while to attend, e.g. We will get back to you within 48 hours with our final decision. a specific reference to something said in a lecture, the readings, or office hours) Provide evidence for why your answer is correct and merits a regrade (i.e. Initiate the regrade through Gradescope (if it is a group project, confer w/ your team first and submit one regrade after your team comes to a consensus). If you think a grading error has occurred please follow these steps: We want to spend that time on regrades where a serious issue has occurred, or with helping students learn the material outside of class. These discussions require a serious investment of time. This is not to discourage students from requesting legitimate regrades, but to discourage students from arguing about 1 point (which is worth 0.05% of your grade). This means your grade can either stay the same, go up, or go down. When we regrade, we closely go through the entire assignment again and reevaluate it as a whole. In our experience less than 3% of the time a regrade results in a change. A grader may incorrectly take off 1-2 points, but they are as likely to give students 1-2 points. The regrade policy is here to protect students from serious issues in grading, not to provide students with a platform to argue about, or plead for an extra point. Ultimately it is your responsibility to check your final grade and get in touch if you believe there is a problem. 
Grades are released on Gradescope often a week after the submission date, typically sooner. Grades are not rounded up, that’s why we have included 5 bonus points. Your letter grade will be determined using the standard grading scale.Final exam date: No final exam, only a final group project.
Cogs 185 ucsd how to#
Describe potential pitfalls of data analyses, how to identify them, and how to avoid themĥ Reading Quizzes (lowest quiz score dropped).Demonstrate how to think critically about data, and how to approach problems with a “data-first” mindset.Communicate data-related topics and projects.Identify data science questions and the appropriate analytic approach to answering those questions.Discuss data privacy and ethical concerns with real-world examples.Comprehend core data science concepts and examine their applications.Assignments and the final are submitted through Gradescope.Reading quizzes and the exam are taken through Gradescope.All course materials are provided through this website.
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