Course ObjectivesThe mathematics of modern computer science is built almost entirely on discrete math, in particular topics like combinatorics and graph theory. The current hot topics of big data and machine learning rely heavily on a good grasp of probability. The basics of probability will be taught in this course. In order to learn the fundamental algorithms used by computer programmers, you will need a solid background in these subjects. CIT 592 is designed to give you a strong fundamental knowledge of these discrete math concepts.
This course also prepares you to take the more advanced theoretical computer science courses such as CIS502 (algorithms) Class Meeting TimesTue/Thurs 1:30-3:00pm, Venue TBD
Recitation on Tuesday 4:30-6pm, Venue TBD
Back to Top TextbooksIn terms of actual physical textbook for this class, it is tough to find something that works really well for MCIT students. We will be scanning relevant pieces of various textbooks and putting them on canvas. We will, however, be using an online interactive textbook (Zybook) to get the basic principles across. This text is mandatory To get this textbook here is the 3 step process
Back to Top PiazzaPlease use the following link to sign up for the piazza discussion for this class piazzaGradingNote that these are only guidelines, but final course grades will likely be based on the following:
Important:Credit for work will be recorded only as reported by the TA in the Gradebook on Canvas. It is your responsibility to make sure that your work has been properly recorded in the Gradebook. Make sure you notify the TA of any problems regarding missing records or incorrectly entered scores; the grade entries on the Canvas will be considered permanent one week subsequent to their posting. Our TAs will be responsible for adjudicating problems related to grading; the instructor will only be involved as a possible court of last appeal in case there is some truly difficult decision to make (i.e., in most cases, I will not be willing to second guess the TAs' decisions). To submit a request to the TA for a regrade of an assignment, email the TA stating the nature of the problem and the remedy you desire. You must submit this adjustment request within one week of the return of the material in question. The TAs will not consider any requests for grade adjustments that are submitted later than this one week grace period. Back to Top Academic IntegrityDo not cheat. Please note that searching for solutions online is the same as cheating. If you ask your classmates for help, it has to be at the conceptual level and not the actual question on the HW. Also, you HAVE to tell us who helped you out. Note: When in doubt always ask the instructor or TA first, to avoid any potential collabration that can lead to academic dishonesty. You can further read Penn's Code of Academic Integrity page on this subject matter, as well as the SEAS Graduate Student guidelines on the code of ethics. Back to Top Homework turn-in procedureHomework has to be submitted online on canvas. Each homework will have a deadline that canvas will be keep track of. No hand-written submissions will be accepted. Do not take an image of your hand written submission and submit that image either. All HWs in this course have to be submitted in pdf form. No other extension is allowed. You have 4 late days that you can use over the course of the semester. Please budget them wisely. I would strongly recommend leaving them for later HWs since the final weeks of the semester tend to be the crazier ones. Importantly, please note that if the HW is due at 11:59 pm on Tuesday and you submit it at 10 minutes past midnight on Wed (0010 hrs on Wed), then it will be considered late.If you run out of late days and submit a HW late, you will incur a 50% penalty on the HW. You are still encouraged to submit the HW though, since any score is infinitely (mathematically speaking) better than a 0. Back to Top |