- Lectures: Tue/Thurs 3:30-5:20pm in Bishop Auditorium (watch online)
- Sections: Fri 3:30-4:20pm in Skilling Auditorium; see calendar for schedule.
- Office hours: CA office hours locations are TBA; see calendar for times; see [Office Hour Logistics] for logistics.
How to contact us:
Please use Piazza
for all questions related to lectures, homeworks, and projects, and to
find announcements. For external queries, emergencies, or personal matters that you don't
wish to put in a private Piazza post, you can email us at email@example.com
For SCPD-specific issues, email firstname.lastname@example.org
or call 650-741-1542.
All announcements will be made on Piazza
. NOTE: If you enrolled in
this class on Axess, you should be added to the Piazza group automatically,
within a few hours. You can also register independently; there is no access code required to join the group.
: look here
for dates/times of all lectures, sections, office hours, due dates.
What is this course about?
What do web search, speech recognition, face recognition, machine translation,
autonomous driving, and automatic scheduling have in common?
These are all complex real-world problems,
and the goal of artificial intelligence (AI) is to tackle these
with rigorous mathematical tools.
In this course, you will learn the foundational principles that drive these
applications and practice implementing some of these systems. Specific
topics include machine learning, search, game playing, Markov decision
processes, constraint satisfaction, graphical models, and logic.
The main goal of the course is to equip you with the tools to tackle new
AI problems you might encounter in life.
This course is fast-paced and covers a lot of ground,
so it is important that you have a solid foundation on both the theoretical and empirical fronts.
You should have taken the following classes (or their equivalents):
There is no required textbook for this class, and you should be able to
learn everything from the lecture notes and homeworks.
However, if you would like to pursue more advanced topics or get another
perspective on the same material, here are some books:
Bear in mind that some of these books can be quite dense and use different
notation terminology, so it might take some effort to connect up with the
material from class.
Finally, to look at course content from the last offering (Spring 2019), click here.
A note on the Summer schedule:
CS 221 is also offered during the Fall and Spring quarters, during which classes last ten weeks. In the Summer edition, we will cover the same material, but do so in only eight weeks (with more lecture time per week). Due to this compressed schedule, it is even more important that you have mastered the prerequisite material.
- Homeworks (70%):
There will be weekly homeworks with both written and programming parts.
Each homework is centered around an application and will also deepen your understanding of the theoretical concepts.
Some homeworks will have a competition component; winners will receive extra credit.
All assignments are due at 3pm on the due date (30 minutes before class).
Here are all the homework deadlines:
- Exam (30%): The exam is a three-hour written exam that will
test your knowledge and problem-solving skills on all preceding lectures and homeworks.
You cannot use any external aids
except one double-sided page of notes.
If you have a request for OAE accommodations or a major conflict (e.g., an academic conference) complete this Google Form by Thursday, July 18.
Date: Friday, August 16 from 7pm to 10pm
Location: Cubberley Auditorium
For SCPD students, your exams will be distributed through the SCPD office once you have set up an exam monitor.
You will be awarded with up to 2% extra credit
if you answer other students' questions in a substantial and helpful way.
Homeworks should be written up clearly and succinctly; you may lose points if your answers
are unclear or unnecessarily complicated.
Here is an example
of what we are looking for.
You are encouraged to use LaTeX to writeup your homeworks
(here's a template
), but this is not a requirement.
The grader runs on Python 2.7, which is not guaranteed to work with newer versions (Python 3) or older versions (below 2.7).
Please use Python 2.7
to develop your code.
The programming assignments are designed to be run
in GNU/Linux environments, such
Most or all of the grading code may incidentally work on other
systems such as MacOS or Windows, and students may optionally
choose to do most of their development in one of these alternative
environments. However, no technical support will be provided for
issues that only arise on an alternative environment. Moreover,
no matter what environment is used during development, students
must confirm that their code (specifically, the original
operating on the student's
submission.py) runs on a GNU/Linux server,
The submitted code will not be graded if it has one of the following issues:
- The original
grader.py script (operating on the
submission.py) does not exit normally.
Note that calls such as
os._exit() may cause the program to exit abnormally, as may excessive resource usage.
Also note that Python packages outside the standard library are not guaranteed to work.
- The code reads external resources other than the files given in the assignment.
- The code is malicious. This is considered a violation of the honor code.
The score of the assignment will be zero (0) and the incident will be reported to the Office of Judicial Affairs.
Collaboration policy and honor code:
You are free to form study groups and discuss homeworks and projects.
However, you must write up homeworks and code from scratch independently, and you must acknowledge in your submission all the students you discussed with.
The following are considered to be honor code violations:
- Looking at the writeup or code of another student.
- Showing your writeup or code to another student.
- Discussing homework problems in such detail that your solution (writeup or code) is almost identical to another student's answer.
- Uploading your writeup or code to a public repository (e.g. github, bitbucket, pastebin) so that it can be accessed by other students.
- Looking at solutions from previous years' homeworks - either official or written up by another student.
When debugging code together, you are only allowed to look at the input-output behavior
of each other's programs (so you should write good test cases!).
It is important to remember that even if you didn't copy but just gave
another student your solution, you are still violating the honor code, so please be careful.
We periodically run similarity-detection software over all
submitted student programs, including programs from past quarters and any
solutions found online on public websites.
Anyone violating the honor
will be referred to the Office of Judicial Affairs.
If you feel like you made a mistake (it can happen, especially under time
pressure!), please reach out to Robin or the head CA;
the consequences will be much less severe than if we approach you.
All assignments are due at 3pm
on the due date.
Assignments are submitted through Gradescope
If you need to sign up for a Gradescope account, please use your @stanford.edu email address.
You can submit as many times as you'd like until the deadline: we will only grade the last submission.
Submit early to make sure your submission runs properly on the Gradescope servers.
If anything goes wrong, please ask a question on Piazza or contact a course assistant.
Do not email us your submission.
Partial work is better than not submitting any work.
For assignments with a programming component, we will automatically
sanity check your code in some basic test cases, but we will grade
your code on additional test cases.
Important: just because you pass the basic test cases, you are by no
means guaranteed to get full credit on the other, hidden test cases, so you should
test the program more thoroughly yourself!
Unless the assignment instructs otherwise, all of your code modifications
should be in
submission.py and all of your written answers
<assignment ID>.pdf. Upload the former to Gradescope
under the "Programming" section, and the latter under the "Written" section.
An assignment is $\lceil d \rceil$ days late if it is turned in $d$ fractional days late
(note that this means if you are $1$ second late, $d = 1/(24 \times 60 \times 60)$ and it is 1 day late).
You have seven (7) late days
in total that can be distributed among the assignments without penalty.
There is a maximum of two (2) late days that can be used per assignment.
If you exceed this limit by $k$ hours,
then you will incur a multiplicative penalty factor of $\max(1 - k/5, 0)$.
For example, if you get $40$ points and turn in your homework 2 days + 1.5 hours after the deadline,
then your effective score is $40(1 - 1.5/5) = 28$.
If you exceed $5$ hours, you will receive $0$ points.
You get a zero after all your late days run out, but we reserve the right to give partial credit in extenuating circumstances.
Regrades: If you believe that the course
staff made an objective error in grading, then you may submit a
regrade request. Remember that even if the grading seems harsh to
you, the same rubric was used for everyone for fairness, so this
is not sufficient justification for a regrade.
It is also helpful to cross-check your answer against the released solutions.
If you still choose to submit a regrade request, click the corresponding
question on Gradescope, then click the "Request Regrade" button at the
Any requests submitted over email or in person will be ignored. Regrade requests for a
particular assignment are due by Sunday 11:59pm, one week after the
grades are returned. Note that we may regrade your entire submission,
so that depending on your submission you may actually lose more points
than you gain.