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JOHN CABOT UNIVERSITY
COURSE CODE: "CS/PS 302"
COURSE NAME: "Artificial Intelligence Concepts"
SEMESTER & YEAR:
Spring 2026
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SYLLABUS
INSTRUCTOR:
Alice Fabbri
EMAIL: [email protected]
HOURS:
TTH 4:30 PM 5:45 PM
TOTAL NO. OF CONTACT HOURS:
45
CREDITS:
3
PREREQUISITES:
One previous course in Computer Science or Psychology
OFFICE HOURS:
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COURSE DESCRIPTION:
Artificial Intelligence encompasses the theory and development of computer systems able to perform tasks normally requiring biological intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. This course will engage students in a discussion of the key methods used and results reported in this rapidly evolving field. We will also consider the relationships between artificial and biological intelligence – both what they are and what they could or should be – as well as the philosophical and ethical challenges raised by the recent, explosive progress in artificial intelligence research.
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SUMMARY OF COURSE CONTENT:
This course explores the field of Artificial Intelligence, beginning with its classical foundations centered on intelligent agents, search, and knowledge-based systems using logical and probabilistic reasoning. The course then shifts its focus to the modern era of AI, focusing on powerful Machine Learning paradigms, including Deep Learning and Reinforcement Learning. The final section explores contemporary applications across Natural Language Processing and Computer Vision, demonstrating how these techniques solve complex real-world problems.
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LEARNING OUTCOMES:
- Understand how intelligent agents operate, interact with their environments, and leverage search techniques to solve problems.
- Discern the core concepts, strengths, and limitations of different AI approaches, from classical reasoning (logic/probability) to modern Machine Learning.
- Grasp the workings of contemporary AI fields, including Deep Learning, Reinforcement Learning, NLP, and Computer Vision.
- Determine how AI techniques can be ethically and practically leveraged, and demonstrate the capacity for independent research on novel AI topics.
- Demonstrate awareness of the evolutionary path, societal implications, and ethical challenges posed by modern AI systems.
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TEXTBOOK:
| Book Title | Author | Publisher | ISBN number | Library Call Number | Comments | Format | Local Bookstore | Online Purchase |
| Artificial Intelligence: A Modern Approach, 4th Edition | Stuart J. Russell and Peter Norvig | Pearson | 978-1292401133 | | | | | |
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REQUIRED RESERVED READING:
RECOMMENDED RESERVED READING:
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GRADING POLICY
-ASSESSMENT METHODS:
| Assignment | Guidelines | Weight |
| Project | Students will test an artificial intelligence technology | 25% |
| Homeworks | There will be four assignments | 20% |
| Midterm | Written exam | 20% |
| Final exam | Final written an exam with questions on all the topics covered during the course | 25% |
| Participation | Students should demonstrate that they have read and (at least tried to) understand the material that we are discussing | 10% |
-ASSESSMENT CRITERIA:
AWork of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensive knowledge of relevant information or content. The student demonstrates complete, accurate, and critical knowledge of all the topics, and is able to solve problems autonomously
BThis is highly competent level of performance and directly addresses the question or problem raised. There is a demonstration of some ability to critically evaluate theory and concepts and relate them to practice. The work does not suffer from any major errors or omissions and provides evidence that the student uses clear logic in his/her arguments.
CThis is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures. Mathematical statements are properly written most of the time.
DThis level of performances demonstrates that the student lacks a coherent grasp of the material. Important information is omitted and irrelevant points included. Many mistakes are made in solving the problem raised. In effect, the student has barely done enough to persuade the instructor that s/he should not fail.
FThis work fails to show any knowledge or understanding of the subject-matter. Most of the material in the answer is irrelevant.
-ATTENDANCE REQUIREMENTS:
ATTENDANCE REQUIREMENTS AND EXAMINATION POLICY
Full credit for attendance will be given to students with three or fewer unexcused absences. Four or more absences will result in a proportional reduction of the grade. Coming late to class or leaving early will be possible only with permission of the instructor.
Major exams cannot be made up without the permission of the Dean’s Office. The Dean’s Office will grant such permission only when the absence was caused by a serious impediment, such as a documented illness, hospitalization or death in the immediate family (in which you must attend the funeral) or other situations of similar gravity. Absences due to other meaningful conflicts, such as job interviews, family celebrations, travel difficulties, student misunderstandings or personal convenience, will not be excused. Students who will be absent from a major exam must notify the Dean’s Office prior to that exam. Absences from class due to the observance of a religious holiday will normally be excused. Individual students who will have to miss class to observe a religious holiday should notify the instructor by the end of the Add/Drop period to make prior arrangements for making up any work that will be missed.
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ACADEMIC HONESTY
As stated in the university catalog, any student who commits an act of academic
dishonesty will receive a failing grade on the work in which the dishonesty occurred.
In addition, acts of academic dishonesty, irrespective of the weight of the assignment,
may result in the student receiving a failing grade in the course. Instances of
academic dishonesty will be reported to the Dean of Academic Affairs. A student
who is reported twice for academic dishonesty is subject to summary dismissal from
the University. In such a case, the Academic Council will then make a recommendation
to the President, who will make the final decision.
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STUDENTS WITH LEARNING OR OTHER DISABILITIES
John Cabot University does not discriminate on the basis of disability or handicap.
Students with approved accommodations must inform their professors at the beginning
of the term. Please see the website for the complete policy.
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SCHEDULE
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Week 1 to Week 4:
- Introduction
- Intelligent agents
- Search techniques
Week 5 to Week 7:
- Logic
- Knowledge bases and manipulation
- Planning
Week 8 to Week 9:
- Probabilistic reasoning
- Decision-making under uncertainty
Week 9 to Week 11:
- Machine learning
- Deep Learning
- Reinforcement Learning
Week 12 to Week 14:
- Natural Language Processing
- Computer Vision
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