|
|
Role |
Office
hours |
Office
location |
E-mail
address |
Phone |
|
|
Jicheng Fu |
Professor |
Monday, Wednesday, and Friday: 1:00 – 1:40 pm |
STEM237 |
974-5704 |
Lecture Time & Location: Monday, Wednesday, and Friday 10:00 am - 10:50 am, MCS113
Course Web Page: https://cs2.uco.edu/~fu/SE4443/underindex.html
General
questions about the homework assignments should be directed to the instructor
at the above e-mail address. You are encouraged to use the eLearning
discussion group for the course on D2L. Therefore, you should check the
discussion group whenever you have a question about the assignment as someone
else may have already asked it and received an answer.
This course offers an advanced exploration of the integration of cutting-edge AI technologies into modern software systems. Students will engage in in-depth analysis and hands-on experimentation with generative AI frameworks, sophisticated API design and integration, autonomous agent architectures, and techniques for enhancing models with external knowledge across text, image, audio, and video modalities. Students will develop the skills necessary to design, implement, and manage scalable, secure, and ethically grounded AI-driven applications.
Rush Shahani, “Building Reliable AI
Systems”, Manning, ISBN 9781633436732
Upon satisfactory completion of this course, students will be able to
(1) Identify and describe the key components and common design patterns used in integrating AI technologies into software systems, linking foundational theory with practical applications.
(2) Design and develop effective API interfaces and AI-enhanced applications using widely adopted open-source tools and industry-standard frameworks.
(3) Implement deployment strategies that focus on scalability, security, and performance to ensure robust operation of AI-driven systems.
(4) Apply standard testing, benchmarking, and monitoring methods to evaluate AI systems, and utilize gathered data to enhance performance and user experience.
(5) Evaluate the ethical, legal, and social implications of AI integration, proposing responsible and informed solutions aligned with current best practices and regulatory considerations.
SE 4283 Software Engineering I
Homework assignments (40% of the course grade)
There will be a written as well as a programming assignment for each topic.
Since we will be using eLearning (D2L) for submission and grading, you must
upload an electronic copy of your assignment by the due date. For written
assignments, if you choose not to typewrite your assignment, you will need to
scan and upload your submission.
Library assignment (5% of the course grade)
Using
UCO library and database search facilities, locate, access, and read one
article published within five years by the Association for Computing Machinery
(ACM) or by the Institute of Electrical and Electronics Engineers
(IEEE). The article must be relevant to topics of AI Software Systems Integration.
Midterm exam (25% of the course grade)
There will be one in-class midterm exam. The midterm exam is tentatively scheduled on Wednesday, October
21.
Final exam (25% of the course grade)
There will be a comprehensive final exam. Exam date: December 11.
Class participation (5% of the
course grade)
· A student is allowed
to miss two complete classes without penalty. After that, unexcused absence
will be counted.
·
For IVE students:
o
Please use your real name to join
our online sessions
o
If you cannot make
the class, you must watch the course video within 48 hours after the class. Please update your attendance records in
D2L accordingly.
· To improve the
learning quality, students are encouraged to actively ask questions, answer
questions, and get involved in discussions. Attitude is everything.
The written assignments are individual and programming assignments are either individual- or group-based. Each group consists of at most two students.
You are expected to maintain the utmost level of academic integrity in the course, in accordance with the academic integrity policy of the University of Central Oklahoma. In particular, (a) it is your responsibility to protect your work from unauthorized access, and (b) the work you submit is expected to be your own. Academic dishonesty has no place in a university or anywhere else: it wastes our time and yours, and it is unfair to everyone else. Any violation of this code will be penalized, as we take this issue very seriously. Any student observed cheating will receive a grade of zero on the exam or assignment, and the appropriate college administrative personnel contacted. A second offense will result in dismissal from the class with a grade of F.
Barring extenuating circumstances, all assignments must be turned
in on the date specified. You will be given three ''free'' late days, with
the restriction that no more than two free late days can be spent on each
homework assignment. If it is a group assignment, students of the entire group
will be considered using the free late days. After you use up the free late
days, the late submissions will be penalized as follows. Assignments
turned in within 24 hours of the due date will receive 90% of its score.
Assignments turned in within 48 hours of the due date will receive 70% of its
score. Assignments more than 48 hours late will not be accepted.
The
professor will grade your work carefully. However, questions about grading do
occasionally arise. If so, first read the solutions. If questions persist,
please see me of that problem (come to office hours or schedule an
appointment). In the interests of smooth administration and to
encourage you to look at your graded work soon after it is
returned, regrade requests must be made within two weeks
of when the work was returned. We reserve the rights to make
regrade decisions "off-line" (i.e., not immediately at the time
requested).
Due to limitations on the disclosure of
personally identifiable information under certain federal privacy laws,
students are not permitted to record class sessions or allow non-students to
view online class sessions. Sharing links of class videos or add class videos
to a public list is also prohibited. Students registered with the UCO
Office of Disability Support Services may request accommodation of the
prohibition and must present a copy of the DSS letter to the instructor.
The University of Central Oklahoma complies with
Section 504 of the Rehabilitation Act of 1973 and the Americans with
Disabilities Act of 1990. Students with disabilities who need special
accommodations must make their requests by contacting Disability Support
Services, at (405) 974-2516. The DSS Office is located
in the Nigh University Center, Room 305. Students should also notify the
instructor of special accommodation needs as soon as possible. Per Title IX of
the Education Amendments of 1972 (“Title IX”), pregnant and parenting students
may request adjustments by contacting the Title IX Coordinator, at (405)
974-3377 or TitleIX@uco.edu.
The Title IX Office is located in the Lillard
Administration Building, Room 114D.
Important Dates
|
Week |
Dates |
Monday |
Wednesday |
Friday |
|
1 |
08/17-08/21 |
Introduction |
Hallucinations and Reliable AI |
Model Selection and Setting (1) Programming assignment: fundamental python coding with an LLM |
|
2 |
08/24-08/28 |
Model Selection and Setting (2) |
Prompt Engineering (1) |
Discussion and assignment presentation Programming assignment: Model setting & Prompt engineering |
|
3 |
08/30-09/04 |
Labor Day
|
Prompt Engineering (2) |
Discussion and assignment presentation Programming: Deploy your own local LLMs |
|
4 |
09/07-09/11 |
Introduction to RAG |
Data Preparation and indexing for RAG |
Discussion and assignment presentation Programming: Building a RAG System |
|
5 |
09/14-09/28 |
Building a RAG System |
Embeddings & Vector Search (1) |
Progress check, discussion, and problem solving |
|
6 |
09/21-09/25 |
Embeddings & Vector Search (2) |
Exploration of Open-Source Models |
Discussion and assignment presentation Programming: Coding with an Open-Source Model |
|
7 |
09/28-10/02 |
Deploy a local model and equip it with APIs |
Introduction to AI Agents |
Discussion and assignment presentation Programming: Equip a local model with OpenAI-like API |
|
8 |
10/05-10/09 |
Agentic RAG |
Tool Integration with MCP Assignment: Library research |
Discussion and assignment presentation Programming: Tool integration with MCP |
|
9 |
10/12-10/16 |
Introduction to Skills (1) |
Review & Homework Discussion |
Fall Break |
|
10 |
10/19-10/23 |
Introduction to Skills (2) |
Midterm |
Discussion and assignment presentation Programming: Equip your system with Skills |
|
11 |
10/26-10/30 |
Multi-Agent Systems (1) |
Multi-Agent Systems (2) |
Discussion and assignment presentation Programming: Build a multi-agent system |
|
12 |
11/02-11/06 |
Evaluation of Agentic Systems |
Deploying & Monitoring |
Progress check, discussion, and
problem solving |
|
13 |
11/09-11/13 |
Bias, Privacy and Responsible AI |
Ethical discussion |
Discussion and assignment presentation Final Project: A wheelchair navigation system |
|
14 |
11/16-11/20 |
Project development |
Project development |
Progress check, discussion, and problem solving |
|
15 |
11/23-11/27 |
Project development |
Thanksgiving |
|
|
16 |
Review and Discussion |
In-Class Demonstration (1) |
In-Class
Demonstration (2) |
|
|
17 |
12/07-12/11 |
|
Final exam |
|
This schedule (including exam dates) is subject to change. You are
responsible for attending class and staying aware of announced schedule
updates.