General Information
Instructor(s)
Deepak Kumar
202 Park Science Building
526-7485
dkumar at brynmawr dot edu
https://cs.brynmawr.edu/~dkumar/
Lecture Hours: Mondays & Wednesdays from 10:10a to 11:30a
Office Hours: Mondays 4:00 to 5:00p and most Wednesdays (not all) also during Lab Hours.
Lecture Room: Room 337 Park Science Building
Lab:
Laboratories
Texts & Software
Main Texts (Required)
Software
|
  |
|---|
Syllabus
Course Description: Class Number: 2176
Survey of Artificial Intelligence (AI), the study of how to program computers to behave in ways normally attributed to intelligence when observed in humans. Topics include heuristic versus algorithmic programming; cognitive simulation versus machine intelligence; problem-solving; inference; natural language understanding; scene analysis; learning; decision-making. Topics are illustrated by programs from literature, programming projects in appropriate languages and building small robots. Prerequisites: CMSC B151 or CMSC H106/107, and CMSC B231. Haverford: Natural Science (NA) ( ) Enrollment Limit: 24; Enrollment Criteria: Major/Minor/Concentration.
Topics (Ambitious/Tentative List)
| What is AI Turing Test Symbolic versus Subsymbolic AI Narrow versus AGI ELIZA Winograd Schemas The Winters of AI Perceptron Planning/Problem Solving SHRDLU SHAKEY STRIPS Search Algorithms Heuristics Knowledge Representation & Reasoning Logical Reasoning Expert Systems MYCIN R1/XCON DENDRAL CYC |
Knowledge Graphs Commonsense Reasoning Perceptrons Neural Networks Backpropagation Deep Learning Convolution Neural Networks ImageNet Bias in AI Systems Robots Reinforcement Learning Deep Q-Learning AlphaGo Natural Language Understanding Recurrent Neural Networks Word2Vec Watson ChatGPT Explanable AI Neuro-Symbolic Systems Are we there yet? |
Lab Attendance: Attendance in Lab is optional, but will be required during specific weeks. Look for announcements below during the semester. Prof. Kumar will be available in the Lab during all Lab times throughout the semester.
Important Dates
| September 6 | First class meeting |
|---|---|
| October 4 | Exam 1 |
| November 13 | Exam 2 |
| December 11 | Last class meeting |
| December 13 | Exam 3 |
All members of the Instruction Staff are dedicated to the cause of improving diversity, equity, and inclusion in the field of computing, and to supporting the wellness and mental health of our students.
It is essential that all members of the course community – the instructor, TAs, and students – work together to create a supportive, inclusive environment that welcomes all students, regardless of their race, ethnicity, gender identity, sexuality, or socioeconomic status. All participants in this course deserve to and should expect to be treated with respect by other members of the community.
Class meetings, lab sessions, office hours, and group working time should be spaces where everyone feels welcome and included. In order to foster a welcoming environment, students of this course are expected to: exercise consideration and respect in their speech and actions; attempt collaboration and consideration, including listening to opposing perspectives and authentically and respectfully raising concerns, before conflict; refrain from demeaning, discriminatory, or harassing behavior and speech.
Additionally, your mental health and wellness are of utmost importance to the course Instruction Staff, if not the College as a whole. All members of the instruction staff will be happy to chat or just to listen if you need someone to talk to, even if it’s not specifically about this course.
If you or someone you know is in distress and urgently needs to speak with someone, please do not hesitate to contact BMC Counseling Serices: 610-526-7360 (610-526-7778 nights and weekends). If you are uncomfortable reaching out to Counseling Services, any member of the Instruction Staff will be happy to contact them on your behalf.
We understand that student life can be extremely difficult, both mentally and emotionally. If you are living with mental health issues such as anxiety, depression, ADHD, or other conditions that may affect you this semester, you are encouraged to discuss these with the Instructor. Although the details are up to you to disclose, the Instruction Staff will do their best to support and accommodate you in order to ensure that you can succeed this course while staying healthy.
Bryn Mawr College is committed to providing equal access to students with a documented disability. Students needing academic accommodations for a disability must first speak with Access Services. Students can email accessservices@brynmawr.edu to request an appointment to begin this confidential process. If eligible for accommodations as per Access Services, students should schedule an appointment with the professor as early in the semester as possible to share their verification form and make appropriate arrangements. Please note that accommodations are not retroactive and require advance notice to implement. More information can be obtained at the Access Services website. (http://www.brynmawr.edu/access-services/)
Because some students with a disability may be eligible to record lectures - and it is state law in Pennsylvania that individuals are given advance notice that they may be recorded - professors also need to include the following statement in their syllabus:
Any student who has a disability-related need to record this class must first be found eligible to do so by Access Services and must share this eligibility with me, the instructor. Class members need to be aware that this class may be recorded.
Assignments
Lectures
How Nations Are Losing a Global Race to Tackle A.I.’s Harms (NY Times, December 2023)
Submission and Late Policy
No assignment will be accepted after it is past due.
No past work can be "made up" after it is due.
No regrade requests will be entertained one week after the graded work is returned in class.
Any extensions will be given only in the case of verifiable medical excuses or other such dire circumstances, if requested in advance and supported by your Academic Dean.
Communication
As you will discover, we are proponents of two-way communication and we welcome feedback during the semester about the course. We are available to answer student questions, listen to concerns, and talk about any course-related topic (or otherwise!). Come to office hours and labs! This helps us get to know you. You are welcome to stop by and chat. There are many more exciting topics to talk about that we won't have time to cover in-class.
Please stay in touch with, particularly if you feel stuck on a topic or project and can't figure out how to proceed. Often a quick e-mail, phone call or face-to-face conference can reveal solutions to problems and generate renewed creative and scholarly energy. It is essential that you begin assignments early, since we will be covering a variety of challenging topics in this course.
Grading
All graded work will receive a grade, 4.0, 3.7, 3.3, 3.0, 2.7, 2.3, 2.0, 1.7,
1.3, 1.0, or 0.0. At the end of the semester, final grades will be calculated as a weighted average of all grades according to the following weights:
| Exams | 65% |
|---|---|
| Exam 1 | 20% |
| Exam 2 | 20% |
| Exam 3 | 25% |
| Participation & Assignments | 35% |
Incomplete grades will be given only for verifiable medical illness or other such dire circumstances.
Study Groups
All submitted work should be solely your individual work. We encourage you to discuss the material and work together to understand it. Here are our thoughts on collaborating with other students:
If you have any questions as to what types of collaborations are allowed, please feel free to ask.
Created on August 29, 2023.