Syllabus šŸ“–

Table of contents

  1. About 🧐
  2. Communication šŸ’¬
  3. Technology šŸ–„
  4. Class Components šŸŽ
    1. Readings (5%)
    2. Lecture Participation (2%)
    3. Live Practice (8%)
    4. Labs (8%)
    5. Homeworks (16%)
    6. Giving Feedback (1%)
    7. Midterm Exams (60%)
    8. Final Exam
    9. Exam Pass Criterion
  5. Office Hours
  6. Policies āœļø
    1. Grading
    2. Regrade Requests
      1. Sample Regrade Request
    3. A Note on Letter Grades
  7. COLLABORATION POLICY AND ACADEMIC INTEGRITY āš ļøā—
  8. Support šŸ«‚
    1. Food Support for Students
    2. Accommodations
    3. Diversity and Inclusion

About 🧐

Welcome to DSC 20! This class will be different compared to DSC 10, so let’s work together in order to make sure that the transition is as smooth as possible.Ā Do not worry if something does not work right away or you feel lost! We are here to help and guide you through the process.


Communication šŸ’¬

This quarter, we’ll be using Campuswire as our course message board. You will be added at the beginning of the quarter. If you’re not able to access it, please self enroll using a given link, as we’ll be making all course announcements through it.

If you have a question about anything to do with the course — if you’re stuck on a assignment problem, want clarification on the logistics, or just have a general question about data science — you can make a post on Campuswire. We only ask that if your question includes some or all of your code, please make your post private so that others cannot see it. You can also post anonymously if you would prefer.

Course staff will regularly check Campuswire and try to answer any questions that you have. You’re also encouraged to answer a question asked by another student if you feel that you know the answer!


Technology šŸ–„

We will be using several websites this quarter. Here’s what they’re all used for:

  • Course Website: where all content will be posted.
  • Campuswire: discussion forum where all announcements will be sent, and where all student-staff and student-student communication will occur. You should be automatically added to Campuswire.
  • Canvas: where all of the reading quizzes and discussion quizzes will be posted.
  • Gradescope: where all assignments are submitted and all grades live. You should be automatically added to Gradescope; let us know if that’s not the case.
  • Webclicker: where attendance questions are answered in class
  • UCSD Podcast: where lectures and discussion sections are recorded. You may also go to Canvas > Media Gallery. You may search the course code.

If you will not have reliable access to a computer this quarter, please reach out to us ASAP, as the university may be able to accommodate you.


Class Components šŸŽ

Readings (5%)

To prepare you for class sections, there will be readings and/or video watching assignments to be completed before each class. This reading is required and the reading quiz activity will be assigned before each class. Reading quizzes will be done online via Canvas. You will have 3 attempts and the best one will be retained.

Notes:

  • Deadline is the Friday midnight of the week of the lecture. Ideally, submit before each lecture to be in sync with the lecture schedule.
  • Refer to Schedule > Readings column for assigned reading.
  • 3 lowest scores will be dropped.

Lecture Participation (2%)

You will demonstrate lecture participation by engaging with frequent in-class polls. The course will be using the poll software webclicker and as long as you respond to 80% of the questions during a lecture, you will earn the point for the day.

Notes:

  • The first class does not count toward your participation.
  • You have two weeks worth of classes that you can miss without penalty throughout the quarter (i.e. 6 lectures). Does not have to be consecutive.
  • NEW THIS QUARTER: If you score >=93% on a mideterm, I will drop the corresponding weeks.

Process:

  • Before each class you need to join the session using any device with your UCSD email in order to register your vote.
  • Participation scores will be posted periodically to Canvas. You must resolve all issues by the end of Week 1. Failure to ensure that you are getting your participation credit before then will result in a 0 for the days that you have not received credit.
  • You must bring your phone or computer to every class. Forgetting it counts as missing a class.

Live Practice (8%)

Where:

  • PODEM 1A20

When:

  • 3:00-3:50pm

The purpose of these activites is to supplement course content and offer live practice to help with the programming assignments.

Process:

  • You will be divided into groups of two randomly.
  • You will be given problems to work on.
  • Together you should solve these questions and submit them on Gradescope.
  • After the time is up, we will collect your work and staff will go over the solutions.
  • In order to record your participation, you will need to submit your solutions.

Note:

  • 1 lowest (missed Friday) score will be dropped.

Labs (8%)

Weekly labs are a required part of the course and will help you develop fluency in Python. The labs are designed to help you build the skills you need to complete homework assignments. Labs will be due midnight Monday by default (exceptions will be clearly marked on the write-up).

  • Each person must submit each lab independently.
  • Total for all labs is capped at 100%. If your total score is above maximum possible of the lab category (at the end of the quarter), it will be capped to 100%.
  • The lowest lab score will be dropped.

Deadlines and Late Submissions:

  • Labs must be submitted by the midnight (11:59pm) deadline to be considered on time.
  • You may turn them in as many times as you like before the deadline, and only the most recent submission will be graded, so it’s a good habit to submit early and often.
  • Late lab submissions will NOT be accepted.

Lab Regrade Policy

  • You may only regrade labs for errors that are NOT related to your code part. For example, a space is missing in your doctest that prevents the autograder from running.
  • It will cost 1 point to request for such regrades.
  • Please submit your regrade requests within 4 days of grade release.
  • See Regrade Requests for other general information.

Homeworks (16%)

This class will have weekly homework assignments, which will usually be due to Gradescope on Mondays at 11:59pm (exceptions will be clearly marked on the write-up).

  • Total for all homework is capped at 100%. If your total score is above maximum possible of the homework category (at the end of the quarter), it will be capped to 100%.
  • No homework will be dropped.
  • I have a right to interview a student if we find a suspicious assignment.

Deadlines and Late Submissions:

  • Homework assignments must be submitted by the midnight 11:59 pm deadline listed on the write-up to be considered on time. You may turn them in as many times as you like before the deadline, but only the most recent submission will be graded, so it’s a good habit to submit early and often.
  • Homeworks may be submitted up to 24 hours late for no penalty, however late submissions should be reserved for exceptional circumstances. Repeated late submissions may result in course staff reaching out to discuss course progress.
  • Homework submissions after 24 hours late will NOT be accepted.

Homework Resubmission/Regrade Policy:

  • For each homework after the grades are released, you may resubmit the homework once to correct your mistakes within a week (7 days). Style points cannot be redeemed, only autograder points.
  • You will get 80% of your score lost back for resubmission.
  • If your original submission results in autograder failure (e.g. timed out, compile error, etc.), you may additionally ask for a regrade before the resubmission (all within 7 days of grade release).
    • For the first 2 homeworks compile errors and print vs. return issues can be regraded for free.
    • After the first 2 weeks compile errors cost 10 points; print vs. return issues cannot be regraded if the write-up explicitly says return or print (use the resubmission attempt).
    • If there are issues that are out of your control, we may regrade your submission for free.
  • Important: Please test your code locally before uploading and wait for the autograder message before you leave Gradescope.
  • See Regrade Requests for other general information.

Giving Feedback (1%)

Since I included a few major components in this iteration of the class, I’d like to make sure that the class reflects your expectations. I will check in with you periodically and would like to reward you for your time.

Midterm Exams (60%)

There will be three exams this quarter. All of them are during the lecture time and in person:

  • Exams 3 X (20%): during lecture, in person.
  • This category is also capped at 100%.

Final Exam

The final exam for DSC 20 is a ā€œno faultā€ final split into three sections:

An optional Exam 1, Exams 2 and Exam 3 ā€œRedemptionsā€ If your score on the exam redemption section is higher than your score on the original exam, it will replace that grade. Getting a lower score on a redemption section cannot hurt you (but it will make us sad). As a consequence, the redemption sections are effectively optional.

Under this policy, a bad performance on an earlier exam can be erased by good performance on the same material in a later exam.

Example: You got an ā€œFā€ on Exam 1 and a ā€œBā€ on Exam 2. You decide to take only the first redemption section on the final (though you could have taken both), and you receive an ā€œAā€. Your midterm scores are now ā€œAā€ and ā€œBā€.

The redemption exams will be held on the date scheduled by the registrar.

Exam Pass Criterion

In order to pass the class, the mean of your three exams scores (after redemption is taken into account) must be 50% or greater.

The reason for this policy is that the exams are the only assessment in this class which you are sure to complete by yourself, and so they are (in theory) the purest measure of your individual understanding. This policy is not meant to be punitive: If your exam scores are not above passing after several attempts, it indicates that you might be better served by retaking the class with a fresh start before moving on to later courses which will draw upon the material from DSC 20.

See Resources for practice exams. All times and content are subject to change.


Office Hours

To get help on assignments and concepts, course staff will be hosting several office hours per week. Some of these will be held remotely and some will be held in person. See the Staff Hours tab of the course website for the most up-to-date schedule and instructions.


Policies āœļø

Grading

Here’s how we will compute your grade.

ComponentWeightNotes
Readings5%drop 3 lowest
Participation2%drop 6 lowest, potentially more
Homework16%none dropped
Live Coding8%drop 1 lowest
Lab8%drop 1 lowest
Exams60%see the Redemption Policy above

Regrade Requests

You can ask for a regrade on lab, homework (or resubmission), and the exams if you believe that the grader made a mistake. Remember that clarity is a part of your score — if you had the right idea but were unable to clearly communicate it, you may still not deserve full credit. We ask that you please submit your regrade requests directly on Gradescope within 4 days of the assignment grade being released. After that, all grades are set in stone.

Sample Regrade Request

  • Please be specific on what you wish to change: line number and detailed content

    Hi, in my hw01, I have accidentally used print() instead of return in my Question 1. I believe it should count as a ā€œPrint vs. Return Issuesā€ on the syllabus so that I would like to request a regrade and receive 25% off.
    Please change my line 20’s print(result) to return result.
    Thanks!

A Note on Letter Grades

We will use a standard scale for assigning letter grades:

Final Grade PercentageFinal Letter Grade
[90% , 100%]Some kind of A
[80% , 90%)Some kind of B
[70% , 80%)Some kind of C
[60% , 70%)D
[0% , 60%)F

Plus and minus cutoffs will be determined at the instructor’s discretion.


COLLABORATION POLICY AND ACADEMIC INTEGRITY āš ļøā—

The basic rule for DSC 20 is: Work hard. Make use of the expertise of the staff to learn what you need to know to really do well in the course. Act with integrity, and don’t cheat.

If you do cheat, we will enforce the UCSD Policy on Integrity of Scholarship. This means: You will fail the course, no matter how small the affected assignment, and the Dean of your college will put you on probation or suspend or dismiss you from UCSD.

Why is academic integrity important? Academic integrity is an issue that should be important to all students on campus. When students act unethically by copying someone’s work, taking an exam for someone else, plagiarizing, etc., these students are misrepresenting their academic abilities. This makes it impossible for instructors to give grades and for the University to give degrees that reflect student knowledge. This devalues the worth of a UCSD degree for all students, making it important for the entire campus to band together and enforce that all members of this community are honest and ethical. We want your degree to be meaningful and we want you to be proud to call yourself a graduate of UCSD!

The Jacobs School of Engineering Code of Academic Integrity, the UCSD Policy on Integrity of Scholarship and this syllabus list some of the standards by which you are expected to complete your academic work, but your good ethical judgment (or asking us for advice) is also expected as we cannot list every behavior that is unethical or not in the spirit of academic integrity. Ignorance of the rules will not excuse you from any violations.

AI Use Policy for This Course

In this course, you are permitted to use AI tools like chatbots (e.g., ChatGPT) and code generators (e.g., CoPilot) only for studying, reflection, and ideation. These tools should support your learning, but they should not generate content for assignments. If you choose to use AI, you must track your usage by citing the tool, dates of use, and any relevant prompts. Be prepared to share this process with me as part of your documentation.

This policy helps ensure the skills and strategies taught in this course are mastered without undue reliance on AI. Our focus is on your original work, which allows for meaningful feedback and personal growth. If you ever feel overwhelmed, please reach out to me or the teaching team. We understand the pressures of university life and are committed to working with you to find solutions, including extensions or assignment adjustments.

Fairness and responsible use of AI apply to everyone in this class, including me. I commit to adhering to these same principles when using AI tools in my teaching. Let’s work together to create a supportive and successful learning environment!

What counts as cheating?

In DSC 20, you can read books, surf the web, talk to your friends and the DSC 20 staff to get help understanding the concepts you need to know to complete your assignments. However, all code must be written by you, together with your partner if you choose to have one (when allowed). Note that a partner is allowed only when we explicitly say that groupwork is allowed for a particular assignment. Most assignments in this course must be completed individually.

The following activities are considered cheating and ARE NOT ALLOWED in DSC 20 (This is not an exhaustive list):

  • Using or submitting code acquired from other students (except your partner, where allowed), the web, or any other resource not officially sanctioned by this course

  • Having any other student complete any part of your assignment on your behalf

  • Acquiring exam questions or answers prior to taking an exam

  • Completing an assignment on behalf of someone else

  • Providing code, exam questions, or solutions to any other student in the course

  • Using any external resource on closed-book exams

The following activities are examples of appropriate collaboration and ARE ALLOWED in DSC 20:

  • Discussing the general approach to solving homework problems or a final project (when given)

  • Talking about debugging strategies or debugging issues you ran into and how you solved them

  • Discussing the answers to exams with other students who have already taken the exam after the exam is complete

  • Using code provided in class, by the textbook or any other assigned reading or video, with attribution

  • Google searching for documentation on Python

How can I be sure that my actions are NOT considered cheating?

To ensure that you don’t encounter any problems, here are some suggestions for completing your work.

  • Don’t look at or discuss the details of another student’s code for an assignment you are working on, and don’t let another student look at your code.

  • Don’t start with someone else’s code and make changes to it, or in any way share code with other students.

  • If you are talking to another student about an assignment, don’t take notes, and wait an hour afterward before you write any code.

Note: in the discussion above, we are talking about other students that are not your pair programming partner. See the pair programming guidelines for information on working with a partner.

Remember, Academic Integrity is about doing your part to act with Honesty, Trust, Fairness, Respect, Responsibility and Courage.


Support šŸ«‚

Food Support for Students

If you are skipping and stretching meals, or having difficulties affording or accessing food, you may be eligible for CalFresh, California’s Supplemental Nutrition Assistance Program, that can provide up to $292 a month in free money on a debit card to buy food. Students can apply at benefitscal.com/r/ucsandiegocalfresh.

The Hub Basic Needs Center empowers all students by connecting them to resources for food, stable housing and financial literacy. Visit their site at basicneeds.ucsd.edu.

Accommodations

Students requesting accommodations for this course due to a disability or current functional limitation must provide a current Authorization for Accommodation (AFA) letter issued by the Office for Students with Disabilities (OSD). This AFA letter should be shared with the instructor and the Data Science OSD Liaison, who can be reached at dscstudent@ucsd.edu. Please contact us by the end of Week 3 to make sure we can arrange accommodations as needed.

Diversity and Inclusion

We are committed to creating an inclusive learning environment in which individual differences are respected and all students feel comfortable. If you have any suggestions as to how we could create a more inclusive setting, please let us know. We also expect that you, as a student in this course, will honor and respect your classmates, abiding by the UCSD Principles of Community. Please understand that others’ backgrounds, perspectives and experiences may be different than your own, and help us to build an environment where everyone is respected and able to thrive.