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CS 188 Summer 2023

Policies

Table of contents

  1. Description
  2. Enrollment
  3. Prerequisites
  4. Communication
  5. Projects
  6. Homeworks
    1. Electronic HW component
    2. Written HW component
  7. Accommodations and Extensions
  8. Lectures
  9. Discussions
  10. Office Hours
  11. Exams
  12. Grading
  13. Collaboration and Ethics
  14. Inclusion

Description

This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm.

By the end of this course, you will have built autonomous agents that efficiently make decisions in fully informed, partially observable and adversarial settings. Your agents will draw inferences in uncertain environments and optimize actions for arbitrary reward structures. Your machine learning algorithms will classify handwritten digits and photographs. The techniques you learn in this course apply to a wide variety of artificial intelligence problems and will serve as the foundation for further study in any application area you choose to pursue.

See the syllabus for slides, deadlines, and the lecture schedule. Readings refer to fourth edition of AIMA unless otherwise specified.

Enrollment

Course staff does not control enrollment; we have to follow the department’s 2022-2023 enrollment policies. We do not have any enrollment codes or any other way to let non-CS majors into the class. If you have any questions about enrollment, please reach out to the emails listed in the enrollment policies page.

Concurrent enrollment applications will be processed in the second week of classes. We will add all pending concurrent enrollment students to the course so you can follow along the first few weeks.

Prerequisites

  • Programming: Prior computer programming experience with python and familiarity with data structures is expected. Students who have taken UC Berkeley courses like CS 61A and CS 61B will be well-prepared.
  • Math: Strong mathematical maturity with probability is expected. Students who have taken UC Berkeley courses like EE 126 or STAT 140 will be well-prepared. A basic understanding of probability (as gained through courses like CS 70 or MATH 55) should be enough for most students in the class. A working knowledge of calculus (as gained through courses like MATH 1B and MATH 53) is also expected.

CS61A AND CS61B AND CS70 is the recommended background.

Course programming assignments will be in Python. Project 0 is designed to teach you the basics of Python and how the CS 188 submission autograder works. Project 1 is a good representation of the programming level that will be required for subsequent projects in this class.

Communication

The course schedule and all resources (e.g. lecture slides, discussion worksheets) will be posted on the course website: https://inst.eecs.berkeley.edu/~cs188/su23/.

All course announcements and content/logistics questions will happen on Ed (the course discussion forum). We will be automatically enrolling everyone.

If you need to contact the course staff privately, please make a private question on Ed or email cs188@berkeley.edu.

All work for this course will be submitted through Gradescope. You can enroll yourself into the Gradescope using the code 6ZY5ZX.

Projects

There are 6 programming projects, submitted on Gradescope. Projects will generally be due on Tuesday.

Projects will by default be graded automatically for correctness, though we will review projects individually as necessary to ensure that they receive the credit they deserve. Projects can be submitted as often as you like before the deadline; we strongly encourage you to keep working until you get a full score.

Project 0 is to be completed alone. All other projects can be completed alone or in teams of two. If done in a team of two, the person who submits needs to tag the other team member on Gradescope. However, it is important that the submission reflects the understanding of both team members. Specifically, it is not acceptable to “take turns” doing alternate assignments; each assignment must reflect significant effort from both team members.

Projects will receive a score of 0 if turned in late. However, you have 5 project slip days, which can extend the deadline for a project by 1 day each. (For example, if a project is due on July 1 11:59 PM, and you submit on July 2 12:30 AM, you will use one slip day.) We will automatically apply slip days to your active project submissions to maximize your total score. Slip days are consumed independently for each partner, but extensions will apply to both. If you need an extension, please use this Google Form and indicate the reason you need for the extension.

Homeworks

There are 7 homeworks, submitted on Gradescope. Homeworks will generally be due on Fridays.

Homework will receive a score of 0 if turned in late. If you need an extension, please use this Google Form and indicate the reason you need for the extension. The lowest Homework score will be dropped from the final grade calculations.

Each homework has two components, described below:

Electronic HW component

The electronic portion will be automatically graded on Gradescope for correctness, and you can submit as many times as you like up to the deadline; we encourage you to work until you have fully solved this portion of the homework.

Written HW component

The written challenge question is meant to make you think beyond the mechanics of what is covered in class and is used to reinforce conceptual material that you will see on exams. For the challenge question only, you must show your work on paper or tablet and submit it to Gradescope. The challenge question will be graded on correctness, and you must show all necessary work to receive full credit. Solutions to the challenge question will be released after the homework is due.

We want you to focus on understanding the material in the homeworks, not necessarily maximizing your score. To that end, we will give full credit on written challenge questions that earn at least 80% of the points possible. Otherwise, the score will be divided by 0.8 (for example, if you get 70% on a written challenge question, your score for that assignment would be counted as 0.7/0.8 = 87.5%).

Homework is to be submitted individually, but may be discussed in groups. If discussed in a group, acknowledge your collaborators in the submission per standard academic practice.

Accommodations and Extensions

As instructors, our goal is to teach you the material in our course. The more accessible we can make it, the better. If you encounter any extenuating circumstances, please let us know as soon as possible so we can best help you succeed in the class.

If you ever need an extension during the semester, please fill out the extensions form.

The Disabled Students’ Program (DSP) supports disabled students at UC Berkeley. They offer a wide range of services and accommodations. If you are facing barriers in school due to a disability, apply to DSP! Students registered with DSP can expect to receive an onboarding email within a week of sending us your formal letter of accommodation through the AIM portal.

Lectures

We will have a 90-minute in-person lecture from Monday to Thursday, 2:00–3:30 PM. This is the listed lecture time on the course schedule.

Lectures will be recorded and recordings will be posted. Lecture attendance is not taken.

Discussions

TAs will hold 1-hour long in-person discussion sections after each lecture. Discussion attendance is optional, but we may offer 3% of extra credit for active discussion participation (this class is NOT curved, see the grading section below). Unless mentioned otherwise, no zoom option or recording will be available.

Office Hours

Office hours and HW/Project parties will happen in-person only. To request help, make a ticket on the office hours queue.

See the course calendar on the website for the office hours schedule locations. Office hours start the week of June 20.

Exams

The midterm is on Monday, July 17, 2023, 7-9pm PT in Wheeler 150.

The final exam is on Thursday, August 10, 2023, 7-10pm PT in VLSB 2050.

The exams will be in-person, butt-in-chair at the assigned time. Please mark your calendars and plan to be present for the exams at the assigned times. THERE ARE NO REMOTE OPTIONS OR ALTERNATE EXAMS. Please do not email the course staff or post on Ed regarding exam logistics, as these will be ignored. More logistics for the exam will be released closer to the exam date.

Grading

Overall grades will be determined from:

  • Projects (25%)
  • Homework Assignments (20%)
  • Midterm (20%)
  • Final Exam (35%)
Grade Overall Percentage
A [93, 100]
A- [90, 93)
B+ [85, 90)
B [80, 85)
B- [75, 80)
C+ [70, 75)
C [65, 70)
C- [60, 65)
D+ [55, 60)
D [50, 55)
D- [45, 50)
F [0 , 45)

Staff may adjust grades upward based on class participation. The grade of A+ will be awarded at staff discretion based on exceptional performance.

If you are taking the class P/NP, you will need to attain a letter grade of C- or higher AND take the final to pass. If you are a graduate student taking the class SUS, you will need to attain a letter grade of B- or higher AND take the final to pass.

Collaboration and Ethics

Please note that obtaining, sharing, and posting solutions to homework or projects is a violation of academic integrity. This includes uploading project code, official solutions, your own solutions, etc. to any site that is accessible by other people, such as a public GitHub repository.

Homework/Project submissions should acknowledge all collaborators and sources consulted. All code and written responses should be original. We trust you all to submit your own work, but to protect the integrity of the course from anyone who doesn’t want to play by the rules, we will actively be checking for code plagiarism (both from current classmates and previous semesters), as well as written homework submissions that look eerily similar.

If you use a code snippet from a website like StackOverflow for a small task (for example, capitalizing a string), this is fine, but please cite your sources in your code with a comment.

Using automatic code generators such as OpenAI Codex and Github Copilot is not allowed.

Exams are expected to demonstrate your work, and your work alone. We have a zero-tolerance policy for any form of collaboration on exams. We are not lenient about cheating; in past semesters, CS 188 has caught upwards of 50 students for academic dishonesty and directly reported them to the Center for Student Conduct. An overwhelming majority (>90%) of the students were found guilty, and thus earned an “F” in the class and a mark on their transcript. Please, just don’t cheat. It’s not cool.

Inclusion

We believe in the crucial importance of creating a learning environment that is welcoming and respectful to students of all backgrounds. The following are specific steps that will help us in achieving this goal:

  • If you feel your academic performance has been impacted negatively due to a lack of inclusion, or due to experiences outside of class such as current events or family matters, please reach out to the instructors and staff. Our job is not only to teach but to support you in every way we can.
  • If something happens in the course that runs counter to the goal of making every student feel safe, respected, and welcome, please contact the head TA or the instructors; if you don’t feel comfortable contacting course staff, you can fill out this form to anonymously let the department know.
  • You may also consult a departmental Faculty Equity Advisor, or fill out the anonymous feedback form for the College of Engineering for equity and inclusion related feedback.
  • If you have a preferred name or set of pronouns that differ from your legal name, you may designate a preferred name for the classroom by following these steps.
  • As a member of the CS 188 community, realize that you have an important duty to help other students feel respected in helping create an inclusive learning environment.