nyu-daniel-zint / intro-to-computer-science-2023-fall

Syllabus

Introduction to Computer Science
New York University
Department of Computer Science

Course description

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Learning objectives

Upon completing this course, students will be familiar with some of the foundations of computer science, including:

• Java programming language
• Primitive data types
• Selections, a.k.a. branching and control statements
• Loops
• Methods
• Single dimensioned arrays
• Mult-dimensional arrays
• Object orientation (i.e. objects and classes)
• Abstract classes and interfaces
• Inheritance
• Strings and text I/O
• Exception handling
• Recursion

Instructor

Daniel Zint
daniel.zint@nyu.edu
60 5th Ave 510

Office hours:

• Monday 4:30 - 5:30 pm
• Wednesday 1:30 - 2:30 pm

Getting help

Help resources available to you are listed in order of urgency of your problem:

Messaging

Our course will use Slack as main communication channel for announcements and discussion. This is a good place to ask questions that anyone - other students, graders, tutors, or the professor - can answer. This is a resource best used when the answer is not required urgently.

Tutoring

Tutors for this course are waiting to answer your questions, either on our message board or during dedicated tutoring hours. Use tutoring for more involved questions and when you prefer a more immediate answer.

Tutoring hours are available on the Brightspace course website.

Talk with the instructor

For any issues at all, contact the instructor:

• see me before class
• raise your hand or simply speak during class
• see me after class
• come to my office hours
• join Slack

Additional tutoring resources

Additional academic support is also available through the University Learning Center.

Attendance & participation

Attendance is highly encouraged! In-class and online message board participation is encouraged. Students who do not attend class regularly and who do not participate in discussions tend to do poorly.

Required software and hardware

All students require access to a computer on which they can write programs using a specific set of applications. Computers at any of the university’s computer labs will do, as will any laptop or desktop computer.

Textbook

The course is based on the book Introduction to Java Programming, Brief Version, 11th Edition written by Y. Liang and published by Pearson. Please get yourself access to a copy of it.

Computer labs

Windows and Mac computers are available to you in the ITS labs. You do not need your own computer nor do you need to purchase any software. However, you will be learning how to use various programs and may wish to have access to them at home or on your laptop. In this case, you must purchase your own license or use a trial version, which is sometimes available from the publisher. You can download software provided by ITS to all students, including SFTP programs, by going to the ITS software page.

Saving your work in the lab

You will be able to save your work in the ITS labs on your own flash drive, or online cloud storage services such as Box.com or Google Drive. Although you can write to the storage drives of the machines in the labs, you cannot be sure that you will have access to the same machine the next time you enter the lab and the drives in the lab are frequently erased.

Grading

You will receive a grade based on the following rubric.

• 10% quizzes
• 15% assignments
• 20% first exam
• 25% second exam
• 30% third exam

Quizzes & Assignments

Quizzes and assignments are completed outside of class in Brightspace.

All assigned work is due before class on the due date indicated on the schedule

There are no extensions.

Regrade requests

If a student requests a regrade of any work, we will regrade the work in full, not just the part that the student believes has been mis-graded.

Academic Integrity

Working with others and leveraging all resources available to you is a prerequisite for success. This is different from copying, cheating, plagiarism, and mental laziness. All submitted work must be your own. There are very reliable systems we use to detect plagiarism in computer code, such as moss and compare50. If you submit any work that is not your own, you risk failure or worse.

Please read the Computer Science department’s policy on academic integrity and the University-wide policy which supercedes it.

Acknowledgements

This course was originally designed by Amos Bloomberg. All course materials were forked from his GitHub repository.