CSCI 100. Information and Intelligence. 3hr; 3cr. No Prerequisites
Information measurement, encoding, and transmission as related to the design of artificial intelligence agents such as search engines, robots, and programs that mimic human intelligence. Models of human and artificial intelligence; relations among information, meaning, and data; diagnostic and causal reasoning in the presence of uncertainty. Readings from the literature of information theory and artificial intelligence; writing assignments, completion of a project to design and/or construct an information-driven intelligent agent.
This is a general education course that may be used to satisfy the Scientific World (SW) requirement under the CUNY General Education structure called Pathways. The course could also be used to satisfy the Natural Science (NS) requirement under the Perspectives curriculum that was in effect at Queens before CUNY introduced Pathways in 2013.
See the General Education website (http://gened.qc.cuny.edu) for more information about the General Education requirements at the college.
The course is offered by the Computer Science Department, and may be used as an elective in the Computer Information Technology (CIT) minor. It does not count as part of the computer science BA or BS majors.
Exam dates, reading assignments, laboratory assignment descriptions, and assignment due dates are all listed on the Course Schedule web page, which gets updated throughout the semester. Bookmark it!
I will send an email message to everyone in the class each time I update the Course Schedule page. If you opt-in to receiving text messages from me, I will also text you when I update it.
There are two 75 minute class meetings per week. Attendance will not be taken (except at the beginning of the semester to verify your registration for the course), but students who often miss class will probably fail the course because (a) exams and assignments depend heavily on material covered only in class and (b) you need to attend class to get credit for brief quizzes and takeaways.
The course requires a regular time commitment from you, 3 hours of class meetings plus 6 hours of “preparation (study, homework) time” each week. This is the standard “Carnegie formula” for college courses: a full-time course load (12 credits) demands as much of your time as a full-time job, so if you take four 3-credit courses each one requires a 9-hour time commitment per week. (4 courses times 9 hours = 36 hours per week.) The difference between college and work, of course, is that no one is keeping track of the time you spend on the job besides you. Instead, you have to manage your time yourself, and you have exams and assignments that assess how you are performing in the course.
Did you ever wonder how your phone, tablet, or laptop does what it does, and does it so well? Did you ever think that computer science requires some special sort of “insider" talent? This course aims to give you a good idea of the answer to the first question, and hopes to convince you that the answer to the second one is “no!”
There are three parts to the course: (1) Code Writing, (2) Information Theory and (3) Artificial Intelligence. Information Theory is the name for the principles that underlie everything we call our “digital world,” from computers, phones, and cameras to appliances, cars, and the Internet. Artificial Intelligence is the part of computer science that builds on Information Theory (among other things) to construct “intelligent agents” that are able to solve complex problems.
Code is what ties everything together in the course. Specifically, you will learn to write code to control a class of computing devices called microcontrollers. Microcontrollers are computers that receive information about the real world from devices that sense things such as light, touch, sound, or temperature. Then, depending on the code that is programmed into them, microcontrollers act on their environment by controlling such things as motors, lights, or speakers.
The particular type of microcontrollers you will work with are called Arduinos, and the programming language you will learn to use is also calld Arduino. By the end of the course, you should be able to construct and program your own Arduino projects using a variety of sensors and actuators. Kinetic art, clothing that responds to what you do or where you are, and simple robots are all examples of the kinds of projects you can work on.
This course is being run as part of a national project called TIDES (Teaching to Increase Diversity and Equity in STEM). STEM is an acronym that stands for Science, Technology, Engineering, and Mathematics: basically, the disciplines in the Division of Mathematics and Natural Sciences at QC. The goal of our particular project is to increase participation by women in computer science. Nationally, women make up only 15-20% of all computer scientists. (Our class is 37% female this semester.) We will spend some of our class time discussing the question of why more women have not been choosing to study computer science.
The course has no other courses as prerequisites: you are not expected to have ever written any code, and you don’t need any mathematical preparation beyond standard arithmetic skills. What you do need is an openness to new ideas, a willingness to think about how our digital world works, and an interest in creating something new.
When the course is offered in the Fall semester, it is coupled with a section of English 110 as part of a Freshman Year Initiative “learning community.” But during Spring semesters the course is open to anyone.
This term we have three people in the course who are computer science majors. They already know how to code, but because microcontrollers are used in ways that are different from desktop, laptop, and mobile computers, they may not have as big an advantage in the course as it might seem. I am hoping they will offer to help other students in the class learn coding concepts.
Each objective will be addressed in overlapping segments of the class meetings. That is, we won’t spend X weeks on one topic, then Y weeks on the next one. Rather, we will be revisiting different parts of each topic throughout the course. The percentages show the approximate amount of class time that will be devoted to each topic.
This class meets Tuesdays and Thursdays from 10:45 to noon in Science Building Room B-141.
Class meetings will normally begin with a brief quiz based on the reading, lecture, and/or video assignments being covered at the time. Classes will aslo normally end with a brief “takeaway” writing exercise in which you summarize your experience in that class. These quizzes and takeaways will be graded on a 3-point scale: “not ok” (1 point); “ok” (2 points); “good” (3 points). Of course if you don’t do an exercise, you get no points for it. At the end of the term all your points will be summed, and the total will count 10% of your course grade. If you get “ok” on everything, you will get full credit for that part of your course grade. “Good” grades are rare, but they can offset missing or “not ok” grades.
There will be homework and laboratory assignments, with midterm and final exams to assess your knowledge of the material covered in the course. In addition, you will work as a team to design and build your own Arduino project for the term. You may work either alone or in a group of 2-3 on your final project.
There are no textbooks for the course. All material you need is available online. See below for some recommended readings.
Classes will consist of a mixture of lectures, laboratory exercises, and discussions in which you are expected to participate actively. You will work on the laboratory exercises in groups of two, but will not necessarily have the same partner for each exercise. You will also be able to do laboratory work outside of class times.
Each semester is a little different, so the following percentages are subject to revision. I will announce any such changes, and will update this list accordingly.
These books are not required, but you may find them useful to consult. Any reading assignments from them will be made available either in the library or as handouts.
Academic dishonesty is prohibited in the City University of New York and is punishable by penalties, including failing grades, suspension, and expulsion. The CUNY Policy on Academic Integrity (http://policy.cuny.edu/manual_of_general_policy/article_i/policy_1.03/text/) defines and gives examples of academic dishonesty and describes the procedures to be followed when cases of academic dishonesty occur.
All programs in New York State undergo periodic reviews by accreditation agencies. For these purposes, samples of student work are occasionally made available to those professionals conducting the review. Anonymity is assured under these circumstances. If you do not wish to have your work made available for these purposes, please let the professor know before the start of the second class. Your cooperation is greatly appreciated.
Students with disabilities needing academic accommodation should register with and provide documentation to the Office of Special Services, Frese Hall, room 111. The Office of Special Services will provide a letter for you to bring to your instructor indicating the need for accommodation and the nature of it. This should be done during the first week of class. For more information about services available to Queens College students, contact the Office of Special Services (718-997-5870) or visit their website (http://sl.qc.cuny.edu/oss/).
During the final four weeks of the semester, you will be asked to complete an evaluation for this course by filling out an online questionnaire. Please remember to participate in these course evaluations. Your comments are highly valued, and these evaluations are an important service both to fellow students and to the institution. Your responses will be pooled with those of other students and made available online, in the Queens College Course Information System (http://courses.qc.cuny.edu). Please also note that all responses are completely anonymous; no identifying information is retained once the evaluation has been submitted.
The Queens College Helpdesk (http://www.qc.cuny.edu/computing/, (718) 997-4444, helpdesk@qc.cuny.edu) is located in the I-Building, Room 151 and provides technical support for students who need help with Queens College email, CUNYportal, Blackboard, and CUNYfirst.