DATASCI 112: Principles of Data Science

This syllabus and everything else you need will be posted on the course website: datasci112.stanford.edu.

Learning Objectives

Acquire and process tabular, textual, hierarchical, and geospatial data.
Uncover patterns by summarizing and visualizing data.
Apply machine learning to answer real-world prediction problems.

Course Staff

Class
Lecture 01 (Mon, Wed, Fri) 11:30 AM - 12:30 PM in 300-300	Andrew Ilyas Wed 10:20AM - 11:20AM Fri 12:30 PM - 1:30 PM in Sequoia 236
Section 02 (Tues, Thurs) 9:30 - 10:20 AM in CoDa B06	Jack Krew Monday 2:30-3:30 PM in CoDa W139	Anya Pinto Wednesday 9:30-10:30 AM in CoDa W139
Section 03 (Tues, Thurs) 10:30 - 11:20 AM in CoDa B06	Zhaomeng Chen Thursday 4:30-5:30 PM in CoDa W139	Claudia Moses Monday 1:30-2:30 PM in CoDa W139
Section 04 (Tues, Thurs) 11:30 - 12:20 PM in CoDa B06	Allison Xu Tuesday 12:30-1:30 PM in CoDa W139	Duru Unsal Wednesday 10:30-11:30 AM in CoDa W139
Section 05 (Tues, Thurs) 3:30 - 4:20 PM in CoDa B06	Xavier Gonzalez Tuesday 4:30-5:30 PM in CoDa W139	Samih Qureshi Monday 3:30-4:30 PM in CoDa W139
Section 06 (Tues, Thurs) 4:30 - 5:20 PM in CoDa B06	Etaash Katiyar Tuesday 3:30-4:30 PM in CoDa W139	Lauren He Tuesday 5:30-6:30 PM in CoDa W139

Contact Outside Class and Office Hours

We prefer to talk to you in person, during class or office hours! But if you need to reach us outside of these times, there are several options:

If you have a question about class logistics or course material, please post it on the Ed Discussion forum so that everyone can benefit from your question.
If you have a private concern, please e-mail the staff list: datasci112-sp25-staff@lists.stanford.edu. Please use this list instead of our individual e-mail addresses for a timely response. You can expect a response within 1 business day.

Grading

Your final grade in the course will be determined from the following components.

Component	Weight
Participation Lecture attendance is expected (although not required). Lectures are not recorded, but we will try to make the slides useful for self-study. Section attendance and participation is required. Do not take this class if you cannot commit to attending every section. If you cannot make it to your assigned section, but you can attend another section on the same day, please e-mail your TA and the TA whose section you plan to attend. You may do this 2x throughout the quarter. If you cannot make it to any sections that day, you may complete the section Colab on your own, and e-mail a PDF to your TA and CA before the following section. They will grade your Colab, and this score will replace your attendance for that day. You may do this 2x throughout the quarter. To allow for emergencies, we will also forgive 2 absences at the end of the quarter. We are effectively allowing you to miss / reschedule up to 6 sections out of 20. If you need to miss more than 6, then you will need to retake this course next quarter.	15%
Labs (posted on the Schedule page) Each lab is a self-contained investigation of a data set. Each lab will be due on Gradescope at 8 AM. Late labs are not accepted under any circumstances. You will always have 1 week to complete every lab, so plan ahead. There will be an optional Lab 6, due in Week 10, that will replace your lowest score from Labs 1-5.	15%
Exams There will be two 50-minute midterms, scheduled for 4/23 and 5/14, during class time.	35%
Final Project	35%
*Total*	100%

Proctoring Pilot

This course is participating in the proctoring pilot overseen by the Academic Integrity Working Group (AIWG). The purpose of this pilot is to determine the efficacy of proctoring and develop effective practices for proctoring in-person exams at Stanford. To find more details on the pilot or the working group, please visit the AIWG's webpage.

Regrade Policy

You may submit regrade requests for labs directly on Gradescope.

For exams, if you believe that we have made a mistake in grading, please fill email andrewi [at] stanford [dot] edu within 1 week of getting the exam back, making sure to include your name and "[Exam X Regrade Request]" in the subject line. Note that we will regrade your entire exam, so your grade could go up or down.

Letter Grades

We only assign a letter grade at the end of the quarter; we do not curve or assign letter grades to individual assignments.

When assigning final letter grades, we will ensure that the median grade among freshmen and sophomores who tried their best is no lower than a B+.

What does "tried their best" mean? Attending class regularly and submitting good-faith attempts on all assignments on time.

Why do we curve the class based on freshmen and sophomores? To make the class more accessible to students with less background. This way, a freshman or sophomore is not penalized if there are a lot of upperclassmen or graduate students (who often have more background) in the class.

How are upperclassmen and graduate students graded? Once we decide the letter grade cutoffs based on freshmen and sophomores, we apply the same cutoffs to upperclassmen and graduate students. So everyone is graded on the same standard.

Disability Accommodations

Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE). Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is being made.

Once you have your letter, please send it to the staff list: datasci112-sp25-staff@lists.stanford.edu. (Please don't email it to the professor or your TA; they will just tell you to e-mail it to this list.)

We need advance warning to prepare for any accommodations, so we must receive your letter by April 11, 2025. For urgent OAE-related accommodations needs that arise after this deadline, please consult your OAE advisor. If you are not yet registered with OAE, contact the office directly at oae-contactus@stanford.edu.