Course Content *

#	Topic	Textbook Reading	Lecture 1	Lecture 2	Lecture 3	Written Assignment	Programming Assignment
0	Introduction	Ch. 1	LE.0.			WA.0.	PA.0. PA.0.1.
Knowledge and Logical Reasoning
1	Propositional Logic	Ch. 7	LE.1.1.	LE.1.2.	LE.1.3.	WA.1.1. WA.1.2.	PA.1.1. PA.1.2.
2	First-Order Logic	Ch. 8	LE.2.1.			WA.2.	PA.2.
3	Inference in First-Order Logic	Ch. 9	LE.3.1.	LE.3.2.	LE.3.3.
4	Knowledge Representation	Ch. 10	LE.4.1.				PA.3.
	Exam 1: Monday, February 6
Uncertain Knowledge and Probabilistic Reasoning
5	Quantifying Uncertainty	Ch. 12	LE.5.1.	LE.5.2.	LE.5.3.	WA.3. Solutions	PA.4. Trace Tables
6	Probabilistic Reasoning	Ch. 13	LE.6.1.	LE.6.2.		WA.4. Solutions	tqdm + pickle + pandas tutorial PA.5.
7	Probabilistic Reasoning over Time	Ch. 14	LE.7.1.	LE.7.2.	LE.7.3.	WA.5.	PA.6. PA.7.
	Exam 2: Friday, March 17
Machine Learning
8	Learning from Examples	Ch. 19	LE.8.1.	LE.8.2.	LE.8.3.	WA.6.	PA.8. PA.9.
	Exam 3: Wednesday, April 5 (Solutions)
9	Deep Learning	Ch. 21	LE.9.1.	LE.9.2.	LE.9.3.	WA.7. WA.8.	PA.10.
-1			LE. -1.0
	Exam 4: Saturday, April 29 (8:30 AM)

* Tentative, subject to change.

Textbook

• Artificial Intelligence: A Modern Approach (4th edition) by Stuart Russell and Peter Norvig

Other Resources

• Jupyter Notebook User Guide
• Python: How to Think Like a Computer Scientist (Swarthmore Edition) by Jeffrey Elkner, Allen B. Downey, and Chris Meyers (free, open textbook)

Class Meeting Times

Lecture: Riley Hall 106
Mondays, Wednesdays, Fridays
10:30 AM - 11:20 AM

Lab: Riley Hall 203
Thursdays
2:30 PM - 4:30 PM

Instructor Information

Dr. Fahad Sultan
Office: Riley Hall 200-D
Phone: 864-294-3755
Email: fahad.sultan@furman.edu
Web: https://fahadsultan.github.io

Office Hours (or by appointment):

Monday: 1:30 PM - 4:30 PM
Tuesday: Drop by office OR email to schedule time
Wednesday: Drop by office OR email to schedule time
Thursday: 8:30 AM - 11:30 AM
Friday: Drop by office OR email to schedule time

Course Description

This is an introductory course in Artificial Intelligence (AI) that aims to teach the fundamentals of AI techniques, focusing broadly on the following five topics:

1. Logical Reasoning over Knowledge Bases
2. Probabilistic Reasoning over Uncertain Knowledge
3. Learning through Pattern Recognition
4. Understanding Natural Language
5. Ethical issues in AI

Course Goals

On successful completion of the course, the students should have the ability to identify, formalize and develop solutions to problems of logical and probabilistic reasoning. Similarly, towards solving problems of learning, prediction and pattern recognition, students should be able to identify and apply appropriate machine learning or deep learning techniques. The course aims to use Natural Language Processing to illustrate how AI techniques can be adapted in various subfields each with its own unique context and data. The course also aims to instill in students a deep sensitivity of the myriad ethical issues raised by AI based systems.

Grading Scale

(Subject to change,
letter grade +/- at instructor's discretion)

A	grade >= 90%
B	80% <= grade < 90%
C	70% <= grade < 80%
D	60% <= grade < 70%
F	grade < 60%

Grading Specifications

Exam 1	15%
Exam 2	15%
Exam 3	15%
Exam 4 (Final)	15%
Written Assignments	15%
Programming Assignments	15%
Class Participation	10%

Minimum Requirements:

In order to pass this class, you must (1) earn a passing grade, (2) submit at least 50% of all in-class submissions, labs, and (3) take all exams. Simply, you cannot blow off an entire aspect of the course and pass this class! Note that this basic requirement is necessary but not sufficient to pass the class.

Lab Times:

The 2-hour lab sessions will be used to introduce programming problems in the weekly assignments. The submission deadline will extend beyond the 2-hr block. Detailed instructions will be provided with each assignment. It is strongly recommended that you bring your laptops during the lab sessions.

Some General Advice:

• Reach Out: It is to your advantage to communicate with me whether in class, in my office, or via email. I plan to maintain an open-door policy between 8:30 AM -4:30 PM, Monday to Friday, unless I am in a meeting or teaching a class. You are strongly encouraged to visit me in my office or request a meeting via email with any questions, comments or observations about the class.
• Come to class and actively participate!
• The assignments and labs are there for you to help learn and gain confidence. Diligent work on these is going to pay off in exams and in your career.
• Start assignments early. This will allow you time to (a) get stuck and recover (b) seek my help, if needed.
• Do not cheat! It is not worth it. Do not overuse your friends or the internet. Come to my office hours or send me an email instead. I know all the answers and am willing to help.

Academic Integrity:

Academic Integrity standards are important to our Furman community and will be upheld in this class. Students should review the Academic Integrity Pledge posted in the classroom and resources available on www.furman.edu/integrity. In this class, the grade penalty for an academic integrity violation is an F for the course. Academic Discipline procedures will be followed through the Office of the Academic Dean.

For programming assignments/homeworks and labs, follow the 50 foot policy in its spirit.

Additional Resources in the Center for Academic Success (CAS; LIB 002):

Peer Tutors are available free of charge for many classes and may be requested by dropping by CAS (LIB 002) or on the Center for Academic Success website. Tutors are typically recommended by faculty and have performed well in the class.

The Writing & Media Lab (WML) is staffed by student Consultants who are trained to help you improve your writing and multimodal communication skills. The consultation process is non-directive and intended to allow students to maintain ownership of their work. In addition to helping with the nuts and bolts, WML Consultants also support you in developing your own ideas thoughtfully and critically, whether you’re writing an essay or planning a video or other multimedia project. You may drop into the WML during its regular hours (LIB 002; 9 AM to 10 PM) or visit the Writing and Media Lab website to make an appointment online.

Professional Academic Assistance Staff in CAS can provide students assistance with time management, study skills, and organizational skills.

The Writing and ESL Specialist provides professional writing support as well as support for students whose primary language is not English.

Accomodations

Furman University recognizes a student with a disability as anyone whose impairment substantially limits one or more major life activity. Students may receive a variety of services including classroom accommodations such as extended time on tests, test proctoring, note-taking assistance and access to assistive technology. However, receipt of reasonable accommodations cannot guarantee success–all students are responsible for meeting academic standards. Students with a diagnosed disability may be entitled to accommodations under the Americans with Disabilities Act (ADA).

Please visit Student Office for Accessibility Resources for more info.

Nondiscrimination Policy and Sexual Misconduct:

Furman University and its faculty are committed to supporting our students and seeking an environment that is free of bias, discrimination, and harassment. Furman does not unlawfully discriminate on the basis of race, color, national origin, sex, sexual orientation, gender identity, pregnancy, disability, age, religion, veteran status, or any other characteristic or status protected by applicable local, state, or federal law in admission, treatment, or access to, or employment in, its programs and activities.

If you have encountered any form of discrimination or harassment, including sexual misconduct (e.g. sexual assault, sexual harassment or gender-based harassment, sexual exploitation or intimidation, stalking, intimate partner violence), we encourage you to report this to the institution. If you wish to report such an incident of misconduct, you may contact Furman's Title IX Coordinator, Melissa Nichols (Trone Center, Suite 215; Melissa.nichols@furman.edu; 864.294.2221).

If you would like to speak with someone who can advise you but maintain complete confidentiality, you can talk with a counselor, a professional in the Student Health Center or someone in the Office of Spiritual Life. If you speak with a faculty member, understand that as a "Responsible Employee" of the University, the faculty member MUST report to the University’s Title IX Coordinator what you share to help ensure that your safety and welfare are being addressed, consistent with the requirements of the law.

Additional information about Furman's Sexual Misconduct Policy, how to report sexual misconduct and your rights can be found at the Furman Title IX Webpage. You do not have to go through the experience alone.