ISE 5745
Transcript Abbreviation:
HumCentMachLearn
Course Description:
Design and analysis of ML for human users. Topics include: introductory machine learning; interactive ML; ethics in AI; human-agent interaction; human-subject research. Students not familiar with Python should enroll in an introductory python course as a pre- or co-requisite.
Course Levels:
Undergraduate (1000-5000 level)
Graduate
Designation:
Elective
General Education Course
(N/A)
Cross-Listings
(N/A)
Credit Hours (Minimum if “Range”selected):
3.00
Max Credit Hours:
3.00
Select if Repeatable:
Off
Maximum Repeatable Credits
(N/A)
Total Completions Allowed
(N/A)
Allow Multiple Enrollments in Term:
No
Course Length:
14 weeks (autumn or spring)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
Distance Learning (100% online)
Prerequisites and Co-requisites:
Prereq: Sr or Grad standing in Engineering.
Electronically Enforced:
No
Exclusions
(N/A)
Course Goals / Objectives:
To be introduced to the basic supervised, unsupervised, and reinforcement learning algorithms.
To understand what algorithms/methods can be used in human-machine systems.
To understand how to design and verify human-machine systems for the human experience.
To interpret ML from a human interaction / ethics perspective.
To design and modify ML algorithms for a better human interaction.
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC | LAB | LAB Inst |
|---|---|---|---|---|
| Ethical Theory, Rhetoric, Human Factors, Interaction Methods | 12.0 | 0.0 | 0.0 | 0 |
| ML: supervised, reinforcement, unsupervised, deep, and XAI | 18.0 | 0.0 | 0.0 | 0 |
| Ethics in AI, Emotion, Trust, Human-subject research, Application | 10.5 | 0.0 | 0.0 | 0 |
| Total | 40.5 | 0 | 0 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| homework | 50% |
| Quizzes (10%) and Exams (20%) | 30% |
| Semester Project | 20% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| material from free online sources. |
ABET-CAC Criterion 3 Outcomes
(N/A)
ABET-ETAC Criterion 3 Outcomes
(N/A)
ABET-EAC Criterion 3 Outcomes:
| Outcome | Contribution | Description |
|---|---|---|
| 1 | Significant contribution (7+ hours) | an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
| 2 | Significant contribution (7+ hours) | an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors |
| 3 | Substantial contribution (3-6 hours) | an ability to communicate effectively with a range of audiences - pre-2019 EAC SLO (g) |
| 4 | Significant contribution (7+ hours) | an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts |
| 5 | Substantial contribution (3-6 hours) | an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives |
| 6 | Significant contribution (7+ hours) | an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
| 7 | Significant contribution (7+ hours) | an ability to acquire and apply new knowledge as needed, using appropriate learning strategies |
Embedded Literacies Info
(N/A)
Attachments
(N/A)
Additional Notes or Comments
(N/A)