Tuesday  - 8:10 - 10:20 PM
Room 130 NE
Spring    2020

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Office: TBD
Office Hours: TBD

1. E-mail related to this course should be sent only to:
2. E-mail sent to any other address will be lost and you will
not receive a response.


IMPORTANT ADMINISTRATIVE INFORMATION

1. Establish a DropBox Account and Link it to my address.
    This way, when you place assignments in your Dropbox  folder , I will be able     to see them.

 
NOTEWORTHY DATES:


COURSE DESCRIPTION

This course will introduce students to the mathematical models, computational methods, and experimental basis for learning processes in biological systems (animals and humans) and how modeling these systems has impacted computational algorithms. The topics that will be covered in this course will include elements of statistical decision theory, adaptive control, machine learning approaches to pattern classification, and neural nets, and will provide a formal structure for solving problems in behavioral, physiological and representation-mediated behavior.

Any acts of disruption that go beyond the normal rights of students to question and discuss with instructors the educational process relative to subject content will not be tolerated, in accordance with the Academic Code of Conduct described in the Student Handbook

Cellular telephones, pagers, CD players, radios, and similar devices are prohibited in the classroom. Calculators and computers are prohibited during examinations, unless specified.

A midterm and final examination will be given in class. Please schedule your other activities in advance. No make-up exams will be allowed without prior arrangements being made.

To prepare for examinations, read the chapters, go over the notes you take in class, and do the assignments. 100 % of the questions are taken directly from the reading material and what is covered in class.

Students will not be given an incomplete grade in the course without sound reason and documented evidence. In any case, for a student to receive an incomplete, he or she must be passing and must have completed a significant portion of the course.

Students are expected to uphold the school’s standard of conduct relating to academic honesty. Students assume full responsibility for the content and integrity of the academic work they submit. The guiding principle of academic integrity shall be that a student's submitted work, examinations, reports, and projects must be that of the student's own work. Students shall be guilty of violating the college’s policy if they:

• Represent the work of others as their own.
• Use or obtain unauthorized assistance in any academic work.
• Give unauthorized assistance to other students.
• Modify, without instructor approval, an examination, paper, record, or report for the purpose of obtaining additional credit.
• Misrepresent the content of submitted work.

Any student violating the colleges academic integrity policy is subject to receive a failing grade for the course and will be reported to the Office of Student Affairs. If a student is unclear about whether a particular situation may constitute violation, the student should meet with the instructor to discuss the situation.

For this class, it is permissible to assist classmates in general discussions of computing techniques. General advice and interaction are encouraged. Each person, however, must develop his or her own solutions to the assigned projects, assignments, and tasks. In other words, students may not "work together" on graded assignments. Such collaboration constitutes cheating. A student may not use or copy (by any means) another's work (or portions of it) and represent it as his/her own. If you need help on an assignment, contact your instructor, not other classmates

In compliance with the Americans with Disabilities Act (ADA), all qualified students enrolled in this course are entitled to “reasonable accommodations.” Please notify the instructor during the first week of class of any accommodations needed for the course

1. COME TO CLASS
2. Take good notes.
3. Ask questions.
4. Do the assignments on time.

Students should prepare to spend at least 3 hours weekly on this material. If you do not have enough time, do not take the course!

1. Contact me if you are confused or fall behind, for whatever reason. Come to my office hours or email me.
2. I get MANY email messages every day, so please keep your message short and to the point. If your message is too long , I probably will not read it.
3. Note that email messages where the sender's name seems fake (e.g., "Mickey Mouse") or the subject is blank or undecipherable, may be automatically filtered out in attempt to eliminate spam and other offensive messages.
4. If I haven't replied to you, please be patient. Sending me multiple copies of the same message (or multiple messages that say the same thing) only clogs my inbox, which takes me longer to get to your message.
5. PLEASE SIGN YOUR EMAIL and mail it to:
   mailto:raphan-7410x@sci.brooklyn.cuny.edu
   This will insure that you are in the class and should be responded to. If you mail to any other address, it will probably not be answered as the system will assume it is SPAM.