Selsky, Michael

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Digital Commons @ New Jersey Institute of Technology (NJIT)

New Jersey Institute of Technology Digital Commons @ NJIT Computer Science Syllabi NJIT Syllabi Fall 2020 CS 100-111: Roadmap to Computing Michael Selsky Follow this and additional works at: https://digitalcommons.njit.edu/cs-syllabi Recommended Citation Selsky, Michael, "CS 100-111: Roadmap to Computing" (2020). Computer Science Syllabi. 187. https://digitalcommons.njit.edu/cs-syllabi/187 This Syllabus is brought to you for free and open access by the NJIT Syllabi at Digital Commons @ NJIT. It has been accepted for inclusion in Computer Science Syllabi by an authorized administrator of Digital Commons @ NJIT. For more information, please contact digitalcommons@njit.edu. CS 100 – Roadmap to Computing Course Syllabus, Fall 2020  Instructor:  Email:  Office:  Office Hours:  Phone:    Classroom Assistant:  Email:   Course Description An introduction to programming and problem solving skills using Python, a very high level language. Topics include:  programming environments and tools, including editor and debugger  basic strategies for problem solving  integer, floating point, string and logical data types  lists, sets and dictionaries  files  conditional, repetition, function and other constructs that control the flow of execution of a program  the design of classes  the use of high level data types such as lists, strings and dictionaries in problem representation.  The course also includes a project in which the student investigates a topic of current interest in computing, writes a report on the topic and presents it in class.  Computing is a profession that requires lifelong learning, which is pursued through activities and using types of materials that are similar to those employed by students. In this course, the student, in addition to mastering the programming and problem solving materials, is expected to learn to effectively use learning strategies and materials — learning how to learn efficiently in preparation for a knowledge intensive profession. This includes effective use of knowledge resources — reading documentation, asking and answering peer questions, consulting with more experienced persons, and searching on-line for answers. It also includes tools and methodology — testing to verify the correctness of code, use of an integrated development environment (IDE) and debugger, writing specifications and documentation.  Learning this material requires extensive hands-on practice. You should plan to spend twice as much time studying and working problems outside of class (that is, about 6 hours a week) as you do in class.  Mode of Instructional Delivery This is a Synchronous Online Course. Lectures are conducted using Webex, a real-time synchronous video conferencing technology.  All exams will be delivered online. Respondus LockDown Browser and Respondus Monitor will be used to ensure the integrity of the online exams. Students are required to have a working webcam and microphone to take an exam. For more information, watch a brief introductory video that explains how LockDown Browser works from the student perspective: https://web.respondus.com/lockdownbrowser-student-video/.   Course Resources The textbook is Think Python by Allen B. Downey, 2nd edition. This is an open source book. It is available without charge in HTML and PDF formats at http://greenteapress.com/wp/think-python-2e/.  A print format is published by O’Reilly (campus bookstore or online). There is also a Kindle edition. The textbook is required. You may use any one (or more) of the formats.  Other course materials:  Python language version 3.8 can be gotten at python.org/downloads. This includes the IDLE development environment, help files, modules and other parts of the standard distribution. You will need to get Python and install it on your personal desktop and/or laptop computer. You can download Python for Windows, Mac or Linux environments. There is no charge for Python.  PythonTutor, a program for stepping through and visualizing the execution of Python code at pythontutor.com.  Wingware 101 IDE, which can be downloaded for various platforms at wingware.com/downloads/wingide-101.  Thonny IDE, downloadable from thonny.org.  The Community Edition of the PyCharm IDE jetbrains.com/pycharm.  The Mu development environment, available at codewith.mu and various other online resources.  Class Attendance Class attendance is mandatory. A student who misses more than five classes will be dropped, without credit. Getting to class late or leaving early counts as half an absence.  Weekly Recitation Meeting with a classroom assistant weekly is an important checkpoint in assuring your grasp of the material being covered and correctly solving assigned problems. When you go for recitation you should have already read the assigned material and worked on current homework. In recitation, you should be prepared to ask the questions you have identified that need clarification. This will check whether your understanding of this material is correct. You may also meet with the instructor for your section. All instructors have posted office hours.  Homework Homework must be submitted through Canvas (and when specified in hard copy) by the beginning of class on the due date. It will not be accepted late except for special circumstances (such as jury duty or medical problem), for which you must provide documentation.  A homework assignment will typically require you to write code that produces a specified output. No credit will be given for code that does not run. Getting a correct solution will often require that your solution be written, tested, and then rewritten multiple times until it fulfills the specification. Expect that the bulk of your time will be spent getting it right. Remember: only code that is correct is worth anything. During the write-test-debug cycle you may — and are encouraged to — use the debugging facilities in the development environment, pose questions on Canvas, and discuss the problem with others.  Roadmap Project Each student will work on a Roadmap project, consisting of a written and an oral presentation, either individually or with a partner. Partners are held to a higher standard than individuals.  Class Participation Presenting your homework answers and presenting your projects in class is a regular part of the course. Asking and answering questions, taking quizzes, solving programming problems — individually or in groups — is a regular part of class meetings.  Cell phones must be turned off during class. During class time you may not play games, text, email, browse the web or engage in other activities that are not part of the class.   Course Communication Canvas (canvas.njit.edu) will be used to post lecture notes, to submit homework and for course discussion. You may also email instructors and classroom assistants.  Collaboration and Individual Responsibility You are encouraged to study and to work on assignments together with others; collaboration is a basic learning technique. You may not take credit for the work of others. You must understand and be able to explain all work that you submit.  What You Will Learn By the end of this course, you will be expected to know and be able to use these pieces of the computing toolkit to compute the solution of a specified problem:   Devise a problem representation (model) and a sequence of steps (algorithm) that correctly solve the problem posed  Write a program that implements the algorithm, using  A core set of Python language elements (keywords, syntax, variables, modules)  Basic data types (integers, floats, strings, booleans, lists, tuples, dictionaries) and operations on them  Statements that perform console/file input and output  Statements that control the sequence of execution (if/else, for, while)  Statements that are structured into function calls  Each homework assignment gives you practice on these concepts and skills, and provides feedback on your progress. You are expected to submit working solutions to every homework assignment. Each element of this course builds on previous material, and any gaps in your understanding will compromise your ability to successfully complete the course. You understand material when you are able to use it to solve problems and to explain your solutions. Each of the two midterm exams and the final exam test your mastery of the material.  Topics to Be Covered The list of topics to be covered includes the following:   Getting Started with Python  Expressions, Variables, and Assignments  Built-in Data Types  Sequence Data Types (Strings, Tuples, and Lists)  Python Standard Library  Formatted Output and User Input  Conditional Execution and Boolean Logic  Iteration  Functions  Argument-Passing and Return Values  Data files  Dictionaries  Designing and Using Classes  Scope and Namespaces  Exceptions  Debugging and Testing   Overall Course Score Formula Homework  12% Attendance  4% Midterm 1  16% Midterm 2  24% Final Exam  36% Roadmap Project  6% Discretionary  2%  The letter grade is based on the overall course score.  Grade Formula Grade A B+ B C+ C D Overall Course Score Cutoff 82 78 74 70 66 62   Common Exams There are two common midterms: Monday, October 19 and Monday, November 16, 4:00pm–5:45pm. The final exam period is December 15–21. The CS100 final exam will be during this period, but the date has not yet been set. Be sure that you will be present for all of your final exams.  You must bring ID to all exams. Students with special needs are advised to make arrangements with the Office of Accessibility Resources and Services, Kupfrian Hall 201.  Exams do not require any portable electronic devices, such as a mobile phone or calculator. It is preferable that you do not bring any such device to the exam, but if you do bring one you must leave it with the proctor during the exam.  There are no makeup exams. If you miss a midterm because of a documented special circumstance you may receive an imputed grade based on the other midterm and the final exam.   Grade Appeals If you believe that you deserve more credit than you have been awarded on a particular common exam problem, you may request, at the time the exam is returned, that it be regraded. Your entire exam will be regraded, which may result in points being added or subtracted.  If you believe that you deserve more credit than you have been awarded on a particular homework problem, you may request, within 48 hours of the grade being posted, that it be regraded. Your entire homework will be regraded, which may result in points being added or subtracted.   University Code on Academic Integrity Read the University Code on Academic Integrity (njit.edu/policies/sites/policies/files/academic-integrity-code.pdf). It describes infractions of academic integrity and penalties for violations, including, for the most serious violations, an XF grade in the course or expulsion. All work that you represent as your own must, in fact, be your own. Work done by others must be given proper credit.   You will be informed of any modifications of this syllabus during the semester. 

CS 100-111: Roadmap to Computing

https://digitalcommons.njit.edu/cgi/viewcontent.cgi?article=1186&amp;context=cs-syllabi

CS 100-111: Roadmap to Computing

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