Syllabus & Course Policies
Overview
Data C88C, also cross-listed as CS C88 and originally offered as CS 88, provides a rigorous introduction to programming, abstraction, and the structure of programs. It is based on CS 61A and covers approximately 70% of the content of that course.
In Fall 2024, Data C88C will have the same instructional team and order of topics as CS 61A, so you can expect a very similar experience in both courses, but Data C88C is 3 units (rather than 4), has 2 lectures per week (rather than 3), has 2 hours of section per week (rather than 3), and has fewer total topics and assignments than CS 61A. Both courses are great for learning about programming. CS 61A moves faster. Students who take Data C88C and want to learn the topics from CS 61A that were omitted can do so by taking CS 47A in a future semester (or just studying on their own).
For the Data Science major and minor, the content in Data C88C is sufficient. For the Computer Science major and minor, the additional content in CS 61A is important. If you are certain that you want to major or minor in Computer Science, CS 61A is the right introductory course.
Students who complete Data C88C can either proceed directly to CS 61B or subsequently take CS 61A, a path that offers a substantial amount of review because of the high topic overlap between the courses. (Review can be very helpful for some students!) However, you cannot take Data C88C for credit after having taken CS 61A.
In Data C88C, we are interested in teaching you about programming, not about how to use one particular programming language. We consider a series of techniques for managing program complexity, such as functional programming and object-oriented programming.
Data C88C primarily uses the Python 3 programming language. Python is a popular language in both industry and academia. It is also particularly well-suited to the task of exploring the topics taught in this course. It is an open-source language developed by a large volunteer community that prides itself on the diversity of its contributors.
Mastery of a particular programming language is a very useful side effect of taking this course. However, our goal is not to dictate what language you use in your future endeavors. Instead, our hope is that once you have learned the concepts involved in programming, you will find that picking up a new programming language is but a few days' work. In fact, we'll learn a second language SQL near the end of the course.
A complete list of lecture topics, readings, and assignments appears in the lecture schedule.
Prerequisites
It is possible to take Data C88C without knowing or learning calculus. Knowledge of calculus concepts will never be required to complete any assignments. However, taking calculus is a great way to practice the arithmetic and algebra that appear regularly in Data C88C.
There is no formal programming-related prerequisite for CS C88C because students without prior experience can succeed in the course, but taking the course without any prior programming experience is typically challenging. Students who take the course without prior programming experience typically must spend more time to complete assignments.
If you find it challenging to complete all of the required coursework in the first three weeks, we strongly recommend that you take another course first. You'll likely have a better experience taking the course later. Taking the course one semester later is unlikely to affect your degree progress or otherwise put you behind, but continuing to struggle despite this recommendation can lead to difficult academic circumstances that can affect your future opportunities. It's better to finish the course with strong mastery of the course material, even if that means delaying by a semester, than to rush through it. At the very least, schedule plenty of time for the course.
Alternative Courses
Here are some alternative UC Berkeley courses that are better suited for students who do not have prior programming experience.
CS 10
CS 10: The Beauty and Joy of Computing is an introductory computer science course which is similar to Data C88C but is designed for students with no prior programming experience. CS 10 covers variables, functions, recursion, algorithmic complexity, object-oriented programming, and many other relevant topics, with the overall content overlap being about 60%. CS 10 starts the semester in Snap!, a block-based programming language which allows students to focus on conceptual understanding without worrying about unfamiliar syntax. After the midterm, the course transitions into Python (the primary language Data C88C uses). CS 10 also covers big ideas and social implications that go beyond programming, showing you the beauty and joy of computing.
Data 8
Data 8: The Foundations of Data Science is an introduction to data science designed to be accessible and useful for all Berkeley students. This course was built for students without prior programming experience. It teaches students to program in Python, but covers a much smaller subset of the language than this course. Most of the course focuses on data processing and statistical techniques that are central to using computers to answer questions about the world. Taking Data 8 before Data C88C is a good way to gain prior programming experience, but taking CS 10 is a better way.
Info 206A
Info 206A: Introduction to Programming and Computation is a 2-unit introduction to programming that overlaps with many topics in Data C88C. Professor Hany Farid has placed all of the videos and exercises for this course online, and these are an excellent resource to supplement Data C88C.
Course Format
The course includes many events and opportunities for learning: lecture, lab, office hours, and more. Try everything out to figure out what combination of these course components help you the most.
Lectures & Videos
There are two 50-minute live lectures per week. In addition, there is a video playlist for each lecture. Please watch the video playlist before attending live lecture or section. The videos cover all required content for the course. Live lecture will not cover all course material and will focus on examples (so watch the videos).
Lab
Weekly lab sections include some review with your TA, a small-group discussion, and a programming-based lab assignment.
There are 10 lab points. Receiving credit for any 10 (or more) labs will earn a perfect lab score for the course.
This semester, we are offering two lab formats: regular lab and the mega lab. Both are designed to help students learn the course material equally well. You can choose which format you want. It is possible to change formats until the course's add/drop deadline.
Regular Lab
In lab, students work with each other to solve problems, including the set of programming problems in each week's lab assignment. To receive credit for lab section, you must complete and submit the lab assignment with all questions answered correctly and you must attend and complete the attendance form.
Mega Lab
Mega lab does not meet on a weekly basis. Students in the mega lab must complete and submit the weekly lab assignment but do not come to lab. You are welcome to ask questions about lab assignments during course office hours. If you need more support than that, you should switch to a regular lab.
Students in mega lab do not need to attend or complete the weekly attendance form to receive credit for their lab assignment. It is up to the mega lab students to keep up with weekly discussion worksheets as they see fit.
Any Zoom-based mega lab meetings will be webcast and recorded.
Choosing a Section Format
Mega lab is only recommended for students with considerable prior programming experience who are confident that they can succeed in the course without the support of in-person lab.
Both options are meant to be great. Mega lab is designed to appeal to students who learn well from watching videos, working independently, and coming to drop-in office hours when they need help. But the smaller format of regular labs has clear advantages for students who wish to work with others and get to know the course staff. Most students choose regular lab.
Office Hours
Office hours are drop-in tutoring sessions in which you can ask questions about the material, receive guidance on assignments, and work with peers and course staff in a small group setting. See the office hour schedule and come by.
Assignments
In addition to programming-based lab assignments, there are programming-based homework assignments and projects.
Homework
Weekly homework assignments let you apply the concepts learned in lecture and section to more challenging problems. Homeworks will typically be released on Wednesdays and be due the following Wednesday.
You are not allowed to use any artificial intelligence tools except for the 61A-bot integrated into ok and VS Code. Starting with Homework 7, students will receive score penalties for doing so. You are also not allowed to use solutions on the internet (of course).
Partial Credit
Homework is scored out of 2 points, and every incorrect question reduces your score by 1 point.
Projects
Projects are larger assignments intended to combine ideas from the course in interesting ways.
You are allowed and encouraged to pair program with a partner. Make sure to alternate roles so that both of you understand the complete results. You may also work alone on all projects, although partners are recommended.
You are not allowed to use any artificial intelligence tools to help you complete projects. You are not even allowed to use AI tools that are available for other parts of the course. It's important to learn how to build these projects on your own. You are also not allowed to use solutions on the internet (of course).
Projects are graded on correctness, with points earned for each problem successfully completed.
Exams
There will be two exams:
- The midterm will be held 8pm-10pm Wednesday 10/30.
- The final exam will be held 3pm-6pm Thursday 12/19.
Exams will be taken on paper on campus in various rooms across campus. There will be no remote exams offered this semester.
Students who are enrolled in another course with a conflicting final exam time may take the Data C88C final exam in the next final exam slot: 7pm-10pm on Thursday 12/19.
We will post an announcement on Ed ahead of each exam with information for students who cannot take the exam.
Excused Exams & Incompletes
Student who are unable to take the midterm for an approved reason may be excused from the exam. If you are unable to take the midterm, please email cs88@berkeley.edu before the exam to describe your situation. Reasons that may be approved include: illness, medical complications, travel, and course conflicts.
If a student is excused from the midterm exam, their exam score will be estimated via regression at the end of the course from their final exam score in a way that does not help or hurt their final grade on average. This method, which assigns them the average score on the missed exam among people who received the same or very similar scores on the final, takes into account variability in exam difficulty.
Typically, students will not be excused from the final exam. However, students who cannot take the final exam for an approved reason and who have completed the assignments for the course may request an incomplete by emailing cs88@berkeley.edu. Students who receive an incomplete grade can complete the course by taking the final exam of a future offering of Data C88C.
Accommodations (DSP and Otherwise)
We will provide appropriate accommodations to all students enrolled in Berkeley's Disabled Students Program (DSP). To ensure that you receive the appropriate accommodations, have your DSP specialist submit a letter confirming your status and accommodations.
If you're not enrolled in DSP, or are in the process of being onboarded by DSP, you may still be eligible for accommodations (such as extended time on exams or extended deadlines). You may also be eligible for accommodations if serious extenuating circumstances should come up during the semester. If you believe you may require accommodations, please email cs88@berkeley.edu.
Assignment Extensions
If you need to request an extension, regardless of your DSP status, fill out the extension request form. Submissions to this form will be visible only to the course instructors, and certain Student Support staff members.
Any extension request up to 24 hours will be approved. Any extension request up to 3 days made by a student with a DSP accommodation for assignment extensions will be approved. Any longer extensions require a strong justification and will be considered on a case-by-case basis. There will never be a penalty for requesting an extension.
Joining Late
Work submitted late will not receive credit, even if it is from a student who joined the course late. However, it is possible to submit assignments if you are not enrolled. Therefore, if you would like to take the course but are having enrollment issues, please submit all assignments by their due date.
To request to be added to course platforms so that you can submit, email cs88@berkeley.edu.
Privacy
All DSP and accommodations-related materials for this course are kept in a repository separate from the rest of the course materials that is visible only to the instructors, selected staff, and staff course managers.
For any DSP and accommodations-related communications, please reach out to cs88@berkeley.edu, which will put you in touch with our student support team. This inbox is only visible to staff members marked with "cs88@" on the staff page. This inbox will be visible to future members of course staff, so if you ever have a communication that you wish to remain private, let us know and we can delete the email exchange once the conversation is resolved.
Resources
Textbook
The online textbook for the course is Composing Programs, which was created specifically for this course, based on the classic textbook Structure and Interpretation of Computer Programs. Readings for each lecture appear in the course schedule. We recommend that you complete the readings before attending lecture.
Past exams appear on the Resources page.
Grading
Your course grade is computed using a point system with a total of 200 points, broken down as follows:
- The midterm, worth 50 points
- The final exam, worth 75 points
- Two projects, worth 45 points
- Homework, worth 20 points
- Lab, worth 10 points
There are 2 extra credit points available to everyone for early submission of projects.
Each letter grade for the course corresponds to a range of scores:
A ≥ 185 A- ≥ 170
B+ ≥ 155 B ≥ 140 B- ≥ 125
C+ ≥ 115 C ≥ 105 C- ≥ 95
D+ ≥ 90 D ≥ 85 D- ≥ 80Your final score will be rounded to the nearest integer before being converted to a letter grade. 0.5 rounds up to 1, but 0.49 rounds down to 0.
The grade of A+ is assigned by discretion of the instructors.
There is no curve; your grade will depend only on how well you do, and not on how well everyone else does. Score thresholds are based on how students performed in previous semesters. Thresholds are not usually adjusted based on student performance and never increased.
Incomplete grades will be granted only for medical or personal emergencies that cause you to miss the final or last part of the course, only for students who have completed the majority of the coursework, and only if work up to the point of the emergency has been satisfactory. If you wish to discuss an incomplete in the course, please contact cs88@berkeley.edu.
There are 11 homework assignments (2 points each) but a maximum of 20 homework points, so you can miss one homework and still have a perfect homework score.
Exam Recovery
It is possible to recover lost points on the midterm by showing improvement on the final. Your score for the midterm (as a percentage of the total points) will be at least 90% of your score on the final exam. For example, a student who scored 10/50 on the midterm (20%), but scored 37.5/75 (50%) on the final exam would receive an adjusted midterm score of 50% * 90% = 22.5/50 points, and so would recover 12.5 midterm points in addition to the 10 midterm points already scored.
Exam recovery only applies to students who take the final exam during finals week. Students who receive an incomplete are not eligible for exam recovery.
Late Policy
If you cannot turn in an assignment on time, you can request an extension. For late work beyond the extended deadline:
- Labs receive no credit.
- Homework receives no credit.
- Projects: Submissions within 48 hours after the deadline will receive 75% of the earned score. Submissions that are 48 hours or more after the deadline will receive no credit.
Citizenship
It is our expectation that all interactions with course staff and other students will demonstrate appropriate respect, consideration, and compassion for others. Please remember to be friendly and thoughtful; our community draws from a wide spectrum of valuable experiences. For further reading, please reference the Berkeley Principles of Community and Berkeley Campus Code of Student Conduct.
For exceptionally rude or disrespectful behavior toward the course staff or other students, your final grade will be lowered by up to a full letter grade (e.g., from an A- to a B-) at the discretion of the course instructors. You don't need to be concerned about this policy if you treat other human beings with even a bare minimum of respect and consideration and do not engage in behavior that is actively harmful to others.
Learning Cooperatively
With the obvious exception of exams, we encourage you to discuss course activities with your friends and classmates as you are working on them. You will learn more in this class if you work with others than if you do not. Ask questions, answer questions, and share ideas liberally.
Learning cooperatively is different from sharing answers. You shouldn't be showing your code to other students or looking at others' code, except:
- During lab, you can share all you want as long as you're all learning.
- For a project that allows partners, you can share anything with your partner.
- If you've finished a problem already, you can look at others' code to help them finish.
If you are helping another student, don't just tell them the answer; they will learn very little and run into trouble on exams. Instead, try to guide them toward discovering the solution on their own by thinking through examples. Problem solving practice is critical to progress in computer science.
Since you're working collaboratively, keep your project partner informed. If some medical or personal emergency takes you away from the course for an extended period, or if you decide to drop the course for any reason, please don't just disappear silently! You should inform your project partner, so that nobody is depending on you to do something you can't finish.
Academic Misconduct
Any students caught collaborating on exams will receive an F in the course. Please don't be one of these students.
Reading others' homework or project solution to a problem before you solve that problem on your own will incur point penalties. You are free to discuss the problems with others beforehand, but you must write your own solutions. The exception to this rule is that you may share code with your project partner.
The following is a list of things you should NOT do. This list is not exhaustive, but covers most of the big offenses:
- Do not copy code from any student who is not your partner.
- Do not allow any student other than your partner to copy code from you.
- Do not copy solutions from online sources such as Stack Overflow, Pastebin, and public repositories on GitHub.
- Do not read others' solutions to an assignment before you have completed the assignment
- Do not post your solutions publicly during or after the semester.
If you find a solution online, please submit a link to that solution anonymously. When we find an online solution, we ask the author to remove it. We also record the solution and use it to check for copying. By reporting online solutions, you help keep the course fair for everyone.
In summary, we expect you to hand in your own work, take your own tests, and complete projects with code written only by you and your partner.
Rather than copying someone else's work, ask for help. You are not alone in this course! The entire staff is here to help you succeed. If you invest the time to learn the material and complete the projects, you won't need to copy any answers.
A Parting Thought
Grades and penalties aren't the purpose of this course. We really just want you to learn. The entire staff is very excited to be teaching Data C88C this semester and we're looking forward to meeting such a large and enthusiastic group of students. We want all of you to be successful here. Welcome to Data C88C!