CSSE 313 - Artificial Intelligence
Rose-Hulman Institute of Technology
Computer Science and Software Engineering Department
Fall 2026/27
Prerequisites
CSSE 230 and a lot of curiosity.
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 four 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.
- Quizzes: Three or four in-class quizzes. The quizzes are
closed book. You may bring a sheet of paper with hand-written notes.
- Participation: This is measured by the number and quality
of participating in class and during class discussions. You may also
raise news items by emailing them to me or mentioning them at the
beginning of class.
| Component | Weight
|
|---|
| Projects | 40%
|
| Quizzes | 15%
|
| Essays | 20%
|
| Cutting-edge work presentation and report | 15%
|
| Participation | 10%
|
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
|
Participation scores are determined as follows. If you have more than
8 abscenses, see below. If you have more than 4 absences, you will get
zero points for attendance, i.e. loose a letter grade. If the above
does not apply to you, then you get 50% of attendance simply for
showing up and looking alert. For the remaining 50%, you need to
actively contribute to the class sessions. You can do this by
regularly contributing to class discussions, by sending the instructor
interesting things related to AI, whether news articles or materials,
among others.
AI Usage
Instructor
I use AI extensively for work and at home; I have experienced AI as a
competent collaborator. I find that when it comes to work, many times,
I end up in a conversation with AI to bring the work to a level that I
find acceptable.
For this course, I use AI to develop learning materials, quizzes, and
assignments. All of those activities require consice prompts,
giving the AI access to existing work, and a fair number of
iterations. I do not use AI to grade assessments or assignments.
Students
I would like you to learn about AI by engaging with it and I would
like you to develop good AI usage habits. As such, you may use AI in
this course. You may use AI to learn the materials and to perform deep
dives into the materials.
For the reading assignments and reviews, please do not use AI. I
would like you to internalize and think about the materials. We will
discuss those articles in class.
The quizzes will be paper-and-pencil, close-book, wiht an 8.5 by
11" sheet of paper wiht anything handwritten on it.
For the experiments, you will be asked to implement several types
of neural networks, and you will be asked to conduct experiments. To
design, implement, and debug your code, you may use AI. The
assignments will offer more details. For the experiments, you may not
use AI. You may not use AI for the first, the Sudoku assignment; that
would take all the fun away...
For the presentations, please see the write-up for details.
When in doubt, please reach out to me.
Attendance Policy/Class Etiquette
The Rose-Human attendance
policy specifies that after 8 excused or unexcused absences you
are liable to fail the course. I will enforce this policy, but will be
happy to make exceptions where warranted.
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.
Please place your phones in your backpack during class. Violations
will incur penalties to your attendance score.
Academic Integrity and CSSE Integrity Committee Procedures
It is critical to maintain academic integrity. It is essential for all
students to cite any and all sources of help received in completing
coursework. This practice not only fosters a culture of honesty and
transparency but also prevents misunderstandings that might otherwise
escalate to formal proceedings. Students should also be aware of what
is appropriate help on homework assignments – see What Constitutes
Misconduct - rev 02-10-2026.docx. To ensure fairness and
responsibility, any instances of suspected misconduct will be handled
through the CSSE Integrity Committee.
If a case of suspected misconduct arises, it will be submitted to
the CSSE Integrity Committee for review (see Integrity
Policy - Procedures - rev 04-27-2026.docx and possible penalties
IntegrityPolicy
- Penalties & Evidence.docx). Exceptions may be made for cases
which the instructor deems minor or which arise late in the term. The
instructor may choose to handle such cases directly (without CSSE
Integrity Committee involvement). The process includes an initial
review of the evidence by the committee, a time for students to
explain or admit to potential misconduct, and potentially a hearing to
examine the circumstances and evidence. Students are encouraged to
continue their studies and engage with the course material and
instructor normally throughout the investigation.