A: Students are expected to have basic programming skills, and know some basic
probability/statistics and linear algebra. You can find a more detailed description
of the prerequisites on the course
Q: I have a time conflict with this course and cannot attend the lectures in person. Is it
still possible for me to take it?
A: Yes it is. This class is recorded and televised by SCPD, and so you will be able to watch the lectures
online at the SCPD site.
Full-time students can access the video lectures here.
Q: How do I submit my homework assignment outside class?
A: If you are a regular (non-SCPD) student and need to submit your homework assignment outside class,
there is a hand-in box in the Gates building, near/outside Gates 188 and 182.
find directions to it here.
Please do not email your homework to us.
If you are an SCPD student, you should email your solutions to us
firstname.lastname@example.org . Write "Problem Set PID Submission" on the
Subject of the email, where PID is the problem set number (1/2/3/4).
Q: Are there any special homework submission instructions for SCPD students?
A: All homeworks should be emailed as a SINGLE pdf file. Additionally, all SCPD students should also include the Homework Routing Form available here. This should appear as the very first page of your Homework solutions. Without the form the staff will be unable to return the graded homework to you.
Q: Will the Friday discussion sessions be recorded?
A: Yes. The discussion sessions will also be available along with the other recorded lectures.
Q: What is the difference between 3 and 4 units?
A: The class can be taken with 3 or 4 units. There is no difference
in workload between them. We'd set it up this way mainly to give people
more flexibility, and you're welcome to pick either. We generally
encourage students to register for 4, but if you'd rather do 3 for any
reason (such as if you have a cap on their number of units), registering
for 3 is fine too.
Q: Is the the same class as the free machine learning class?
A: No, that is a different class, which is not good for Stanford academic
credit. You can learn more about it at www.ml-class.org.