CET4973: Introduction to Artificial Intelligence

General Information

Instructor

Instructor: Prof. Benito Mendoza 
Lecture: Thursday 2:00-5:20 
Classroom: online
Office: V620 
Office Hours: Monday 10:00-11:00, Friday 11:00-12:00, or by appointment.
Email : bmendoza@citytech.cuny.edu 
Phone: 718-260-5885 
Website: http://www.citytech.cuny.edu/faculty/BMendoza

Required Texts [Title. Authors. Publisher. Year.]

  1. No textbook has been adopted. The material will be provided for each topic.

Other Suggested Reference or Supplemented Material

  1. Artificial Intelligence: A Modern Approach (3rd Edition). Stuart Russel and Peter Norvig. Pearson. 2009. ISBN-13: 978-0136042594
  2. Artificial Intelligence in the 21st Century: A Living Introduction, Second Edition. Stephen Lucci and Danny Kopec. Mercury Learning. 2016. ISBN-13: 9781942270003.
  3. Essentials of Artificial Intelligence. Matt Ginsberg. Morgan Kaufmann Publishers Inc. ISBN-13: 9780323139687
  4. A Course in Machine Learning. Hal Daumé III. Self-published http://ciml.info/

Course Overview

Introduction to basic methods of Artificial Intelligence (AI) such as searching, knowledge representation, problem-solving, and learning. Through discussions, small projects, and examples, students learn what AI is, some of the major developments in the field, promising directions, and the techniques for making computers exhibit intelligent behavior. Students make use of available development tools and explore some areas of application such as recommender systems, natural language processing, robotics, and machine learning.

Course Designation: Elective for BTech in Computer Engineering Technology.

Course Credits: 3

Course Learning Outcomes

Course Learning OutcomesUpon successful completion of this course, the students will be able to:

  1. Understand what constitutes “Artificial” Intelligence and how to identify systems with Artificial Intelligence.
  2. Understand the limitations of current Artificial Intelligence techniques.
  3. Familiarity with Artificial Intelligence techniques, such as Neural Networks and Machine Learning.
  4. Recognize how Artificial Intelligence enables capabilities that are beyond conventional technology, for example, prediction and classification, self-driving cars, robotics.
  5. Ability to apply Artificial Intelligence methods and engineering techniques for solving narrowly defined problems.

General Education Outcomes

  • INTEGRATION/ Integrate learning: Resolve difficult issues creatively by employing multiple systems and tools.
  • SKILLS/Communication: Students will develop a written report of a project and an oral presentation for faculty and peers.
  • INTEGRATION/Systems: Understand and navigate systems.

Grading Policy

  • Homework:    40%
  • Labs:                20%
  • Exams:            15%
  • Final Project: 25%
  • Total:             100%
Score % < 60 60-69.9 70-76.9 77-79.9 80-82.9 83-86.9 87- 89.9 90- 92.9 93-100
Grade F D C C+ B- B B+ A- A

Exams

There will be quizzes assigned based on the material covered during the lecture as well as the assigned readings. These quizzes will be taken online using Blackboard during class time.

Labs

There will be different labs assigned where you will apply the lessons learned in class. You must show your program/model/application running to your professor to receive full credit. Late labs will not be accepted and labs will be graded individually, even if you worked in a team.

Final Project

There will be one final project at the end of the semester. This is a team project that culminates with a presentation, a written report, and a demo.

Homework, Exams, Labs, and Final Project

There will be no make-up of missed homework, quizzes, and final project unless you have a valid reason according to City Tech’s policy.

Blackboard

Blackboard will be used extensively to provide course material, collect assignments and reports, and provide detailed grading information. Students must make sure their Blackboard login is working at the beginning of the course.

Other Policies

Attendance

The course abides by the current CUNY Attendance policy. If for any reason you miss a class, it is your responsibility to review all the material covered in the class and to complete the corresponding reading and programming assignments.

In-class Expected Behavior

  • This is an online class so you are expected to have a microphone and a camera for the virtual meetings.
  • Students should show respect to each other and to the professor.
  • Any activity that threatens the college’s academic integrity will result in disciplinary action.
  • Please refer to the Student Handbook and the Catalog of New York City College of Technology for a full listing of the Student Code of Conduct, Classroom Behavior Guidelines, and Academic Integrity Rules.

Academic Integrity Policy

Students and all others who work with information, ideas, texts, images, music, inventions, and other intellectual property owe their audience and sources accuracy and honesty in using, crediting, and citing sources. As a community of intellectual and professional workers, the College recognizes its responsibility for providing instruction in information literacy and academic integrity, offering models of good practice, and responding vigilantly and appropriately to infractions of academic integrity. Accordingly, academic dishonesty is prohibited in The City University of New York and at New York City College of Technology and is punishable by penalties, including failing grades, suspension, and expulsion.

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