Course Information
CSCI1410 is designed for students seeking a broad understanding of Artificial Intelligence. The course surveys many topics in AI, from search and game theory to supervised learning and reinforcement learning.
Lectures take place Tuesdays and Thursdays from 9:00 am to 10:20 am eastern time. The class is offered online this semester. The instructors are Professor Amy Greenwald and Ph.D. student Enrique Areyan Viqueira.
Prerequisites and Required Materials
In Order to take CS1410, you should have already taken CS16, CS18, or CS19. You should have also taken, or can be taken concurrently, one of CS22, CS145, APMA1650, or APMA1655.
The programming language used in this course is Python. We will provide a Python primer at the start of the semester, but knowledge of Python will be required.
The course textbook is Artificial Intelligence, A Modern Approach, 3rd edition by Russell & Norvig. The textbook is available online.
To attend online lectures and TA hours, a computer is necessary, preferably with the Zoom application installed. If you need any assistance (e.g., if you need to borrow a computer from Brown), please contact the HTAs.
Lectures
Lectures are held every Tuesday and Thursday, from 9am to 10:30am ET via Zoom.
Lectures are not recorded. You can access last year's recordings here.
In addition, we are providing slides and recordings from last year covering all lectures, as well as specifically catered notes from this year covering important and new concepts!
Assignments
Assignments are due at 11:59PM ET on their respective due dates. Written portions and resubmissions are due the following day at 11:59PM ET.
For assignment related questions and announcements, check Piazza.
| Homework | Out | Due |
|---|---|---|
| Search | 9/16 | 9/28 |
| Adversarial Search | 9/30 | 10/12 |
| Hidden Markov Models | 10/21 | 11/2 |
| Reinforcement Learning | 11/4 | 11/16 |
| Supervised Learning | 11/18 | 11/30 |
| Final Project | 11/30 | 12/14 |
Resources
The resources below link to course policies and other useful supplementary materials.
Useful Links
Diversity and Inclusion
The computer science department is committed to diversity and inclusion, and strives to create a climate conducive to the success of women, students of color, students of any sexual orientation, and any other students who feel marginalized for any reason. Likewise, our course takes pride in providing an inclusive environment, and welcomes students of all backgrounds. If you feel you have been mistreated by another student, or by a member of the course staff, consider reaching out to one of student advocates on the CS department’s Diversity and Inclusion Committee, or to Professor Greenwald or Professor Cetintemel (the CS department chair). We, the CS department, take all complaints seriously.
Accommodations
If you feel you have any disabilities that could affect your performance in the course, please contact SEAS, and ask them to contact the course staff. We will support accommodations recommended by SEAS.
Harassment
Please review Brown’s Title IX and Gender Equity Policy. If you feel you might be the victim of harassment (in this course or any other), you may seek help from any of the resources listed here.
Hours
Please check the calendar for the latest times and the most updated schedule.
Join the queue using SignMeUp when signing up for hours.
Staff
Amrita Sridhar (ETA)
Andrew Kim (TA)
Daniel Kotroco (TA)
Eli Zucker (TA)
Ella Liang (TA)
Estelle Han (TA)
Ethan Chung (TA)
George Hu (TA)
Jason Crowley (TA)
Jefferson Bernard (TA)
Jinwoo Choi (TA)
Matt Rodrigues (TA)
Matthew Kovoor (TA)
Nathan Tung (TA)
Neil Sehgal (ETA)
Shekar Ramaswamy (TA)
Shreya D'Souza (TA)
Will Hackett (TA)
Husam Salhab (HTA)
Amy Greenwald (Professor)
Enrique Areyan Viqueira (Professor)
Soma Arunkanti Hota (HTA)