CSE 3521
Transcript Abbreviation:
Intr Artif Intell
Course Description:
Survey of basic concepts and techniques in artificial intelligence, including problem solving, knowledge representation, and machine learning.
Course Levels:
Undergraduate (1000-5000 level)
Designation:
Elective
General Education Course:
(N/A)
Cross-Listings:
(N/A)
Credit Hours (Minimum if “Range”selected):
3.00
Max Credit Hours:
(N/A)
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)
12 weeks (summer only)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
In Person (75-100% campus; 0-24% online)
Prerequisites and Co-requisites:
Prereq: 2331 or 5331; and Math 2174 or 2568 or 4568 or 5520H; and Stat 3201 or 3450 or 3460 or 3470 or 4201 or Math 4530 or 5530H; and enrollment in CSE, CIS, ECE or Data Analytics major.
Electronically Enforced:
No
Exclusions:
Not open to students with credit for 5521.
Course Goals / Objectives:
Master basic search techniques for problem-solving, including systematic blind search, heuristically-guided search, and optimal search
Be competent with game tree search methods and the requirements for expert-level game play
Be familiar with using logic and proof as a basis for knowledge representation and automated reasoning
Be familiar with multiple knowledge-representation formalisms
Be exposed to problems in common sense reasoning and language understanding
Be exposed to integrated AI architectures as a platform for building AI systems
Be exposed to machine learning techniques and the kinds of problem they solve
Be exposed to state-of-the-art AI applications related to robotics, machine vision, speech recognition, and computer games
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC out-of-class | REC in-class | Weekly LAB out-of-class | Weekly LAB in-class |
|---|---|---|---|---|---|
| Basic representation and problem solving methods | 6.0 | 0.0 | 0 | 0.0 | 0 |
| Search techniques and game playing | 6.0 | 0.0 | 0 | 0.0 | 0 |
| Knowledge representation using logic, automated proof techniques | 6.0 | 0.0 | 0 | 0.0 | 0 |
| Machine learning, probabilistic inference | 6.0 | 0.0 | 0 | 0.0 | 0 |
| Planning and common sense reasoning | 3.0 | 0.0 | 0 | 0.0 | 0 |
| Perception and communication | 4.0 | 0.0 | 0 | 0.0 | 0 |
| Applications | 6.0 | 0.0 | 0 | 0.0 | 0 |
| AI & Games | 3.0 | 0.0 | 0 | 0.0 | 0 |
| Total | 40 | 0 | 0 | 0 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| Homeworks and Labs | 40% |
| Midterm | 25% |
| Final | 35% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| Artificial Intelligence, A Modern Approach (3rd edition) | Stuart Russell and Peter Norvig |
ABET-CAC Criterion 3 Outcomes:
| Significant contribution (7+ hours) | 1 | Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions. |
| Substantial contribution (3-6 hours) | 2 | Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline. |
| Some contribution (1-2 hours) | 4 | Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles |
| Substantial contribution (3-6 hours) | 6 | Apply computer science theory and software development fundamentals to produce computing-based solutions. |
ABET-ETAC Criterion 3 Outcomes:
(N/A)
ABET-EAC Criterion 3 Outcomes:
| Significant contribution (7+ hours) | 1 | an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
| Substantial contribution (3-6 hours) | 2 | 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 |
| Some contribution (1-2 hours) | 4 | 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 |
| Some contribution (1-2 hours) | 6 | an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
| Some contribution (1-2 hours) | 7 | an ability to acquire and apply new knowledge as needed, using appropriate learning strategies |
Embedded Literacies Info: