CSSE 413 - Artificial Intelligence
Rose-Hulman Institute of Technology
Computer Science and Software Engineering Department
Spring 2024
Prerequisites
CSSE 230 and a lot of curiosity.
Draft Course Desciption
In this course, we will study modern AI systems, their current
accomplishments, positive as well as negative, issues surrounding
their training, and their inner workings. We will formalize those
systems as pattern recognizers and distinguish them from classical,
symbol-manipulating AI. We will study how these systems become so
incredibly powerful through a data driven feature learning. We will
look at how they represent knowledge and study their reasoning
abilities. We will additionally spend some time discussing the
projected impact of anticipated systems and study the building of
beneficial AI systems.
Instructor
Schedule
Please consult the schedule for class materials,
topics covered and assignments.
Grading
Your grade will be calculate based on the following components and
weights. Your assignment scores will be recorded in Moodle.
I will assign grades
according to the following over scores: 90+: A, 87-89.99: B+,
80-86.99: B, 77-79.99: C+, 70-76.99: C, 67-69.99: D+, 60-66.99: D,
0-59.99: F
- Projects. Around five projects related to coding, training,
experimenting with AI systems. Some are pair projects.
- Essays: About seven summaries of key papers in the field.
- Cutting-edge work presentation and report: Presentation of an AI
application that is at the forefront of the field. This is a pair
assignment. You may choose the topic.
- Impact of AI presentation and report: Presentation of an
assigned article concerned with the impact of AI. This is a small team
assignment.
- Take-home final essay: This is a reflective essay on the
learning materials.
| Component | Weight
|
|---|
| Projects | 40%
|
| Essays | 35%
|
| Cutting-edge work presentation and report | 10%
|
| Impact of AI presentation and report | 10%
|
| Take-home final | 5%
|
The course has some activities which are individual ones, auch as the
reviews and some of the programming assignments. Others are team activities,
such as some of the programming assignments and the presentation of current work.
Late Policy. Late work will be scored as follows:
| < 3 hours late | 100% of score
| | 24 hours late | 85% of score
|
| 48 hours late | 50% of score
|
| > 48 hours late | 0% of score
|
Newsgroup
See the Moodle course page.
Attendance Policy/Class Etiquette
Attendance policy
Artificial Intelligence is a fun and interesting topic. I expect
that you participate fully in this class. If you are bored in class,
feel free to suggest ways to make class more interesting.
I expect everyone to be a good citizen, doing things which will aid
in the learning of everyone in this course and avoiding activities which
will distract from them.
Please conduct yourself in class and outside in a manner that is
respectful to yourself and others.
If you feel unwell, for whatever reason, please be a hero and DO
NOT come to class.
Academic Integrity
See the departmental
statement on academic honesty. Dishonesty on any work turned in for
grading may result in a lowered course grade or a grade of an F in the course. If
at any time, you are concerned about whether certain actions of yours
or others, may constitute a violation of this policy, please contact
your instructor.
You may have heard about that new-fangled tool called
ChatGPT. Please do not use it or like tools unless explicitly permitted
in the assignment write-up.
Concerns
While we hope you feel comfortable speaking with any faculty in the
department, if you have a concern and are not sure where to go, the
following CSSE faculty have volunteered to be ombudsmen for the
department: Sid Stamm (F216), Amanda Stouder (F222), Kim Tracy (D216)
and Robert Williamson (F205).