Syllabus

Table of contents

1. Overview
2. Course Meetings
3. Office Hours
4. Grading
5. Assignments
6. Exams
7. Final Grade Calculation
8. Cheating
9. Policy Regarding The Use of Generative AI Tools in this Course
10. Resources

Overview

CSCI100 - Intro to Computer Science (aka CS0) is an introductory class designed for students with no formal exposure to computer science or programming. The goal is to provide a gentle but thorough introduction to computer science that will prepare students to either take further computer science courses, or use computer science in their field of study.

By the end of the course, students will learn

• Variables, Expressions, Types
• Input/Output
• Logic and Control Flow
• Functions
• Algorithms
• Runtime and efficiency
• Sets and Dictionaries
• Computational thinking/Problem solving

Course Meetings

Lectures, labs, and office hours are the main ways in which you will interact with your professor and TAs. You can see the weekly schedule of course meetings on the course schedule page. You must attend the lecture/lab time that you are assigned on Workday.

Lectures

Lectures will be in person twice weekly on Mondays and Wednesdays. During this time we will go over new concepts, review previous concepts, and go through practice scencarios. Students are expected to come to lecture each week, as there be weekly quizzes assigned at a random time during class. Exams and quizzes can only be made up if there is a documented excuse

Labs

Labs this semester will be in person once weekly on Thursdays. During this time we will apply topics taught the two lectures during that week. You will be able to work in pairs during your lab assignments and submit their assignments individually. Labs will be done in Codio and graded by the Codio autograder unless otherwise specified. Labs will be released Wednesday evenings, and will be due the following Friday at 11:59pm Eastern Time.

Labs are a great time to get any questions answered by the instructor, the TAs or your peers, so take advantage of that time!

Office Hours

This semester, there will be a mix of in-person and virtual office hours offered at a wide variety of times. Links for virtual office hours will be found under Calendar on the course website (hucs0.org/calendar). Miss. Orange’s office hours will be held in person in her office, while any in person office hours held by TAs will be at their discretion. You are more than welcome to come to office hours for any reason (talk about assignments, get any logistical questions answered, get career advice, or just to hang out).

The course staff is committed to ensuring that no student falls behind due to lack of resources, so if there’s anything you need help with, please do not stay silent. No question is bad question in this class, and we are more than happy to help you!

Grading

Grading in this course will be done using one of two systems, one that has more weight on exams, and one that has more weight on assignments. The goal for this is to ensure that you are not mainly focused on getting a certain grade, but learning the concepts and applying. Whichever of these two weights are higher for you will be your final grade

Assignments

These details are subject to change during the semester, but the current plan of record is the following:

• ~7 quizzes at random during class time, once a week
• ~10 labs - once a week
• Homeworks - spread throughout the semester
• Projects - spread throughout the semester

Assignments will be due at 11:59pm, with a 10% penalty for each day it’s late, up to 5 days.

Exams

Instead of the traditional 1 midterm and 1 final, there will be 3 exams spaced evenly throughout the semester, with the third exam taking place during finals week. Exam 1 will be Wednesday, September 25th, 2024, Exam 2 will be Wednesday, November 6th, 2024, and the final exam date will be as follows:

Final Grade Calculation

In order to calculate your final grade, the following adjustments will be made:

• Drop 2 lowest quiz scores
• Drop lowest lab score
• Replace Exam 1 with Exam 2 IFF Exam 2 is higher
• Select the higher of the two grading schemes mentioned above.

Per university standards, the following grading scale will be used

‘A’ = 90 or higher

‘B’ = 80-89

‘C’ = 70-79

‘D’ = 60-69

‘F’ = 59 or lower

Cheating

For all assignments in the course, you may discuss approaches with peers or to solving a problem or work in the same room on separate computers to individually solve a problem, but you may not copy and paste code or substantially copy ideas from another student, from online, or from generative AI tools such as ChatGPT or Gemini. It can be tempting to cheat. Know that Codio’s autograder has a very good plagiarism detector. Per Howard University policy, the first time an assignment is found to be plagiarized, the assignment grade will be zero-ed out for all students with matching code. The second time, all students involved will have their final course grade decreased by 1 letter grade (B going to a C, A- does to a B-, etc.). The third time, all students involved will be referred to the Dean’s office for academic dishonesty.

If I ask you how your code works and you do not know, it will be evident that you have copied it. Don’t take the risk. Despite this explicit warning, each year, a few students still cheat and are caught. I do not enjoy catching and penalizing students for plagiarism, but it’s necessary to maintain fairness and hold students accountable for their actions.

The course staff will work tirelessly to provide enough support for any student to get help and make it through the class. In exchange, we ask you to uphold academic integrity and not to plagiarize code or ideas.

Policy Regarding The Use of Generative AI Tools in this Course

As mentioned in the Cheating section above, you may not use generative AI tools to do assignments for you. That does not mean that this course is a 0% AI usage class, however. You are free to use generative AI tools to help you understand concepts, with the understanding that products like ChatGPT and Gemini are not 100% accurate, and will possibly give you incorrect responses. There will also be instances where you will be asked to use GenAI tools for certain problems/assignments to get learn more about how to use them properly and understand their limitations, and those instances will be clearly conveyed to you.

Resources

Along with office hours, there will be numerous resources provided to you to aid in your learning and career goals. Some of them are listed below, but there will be more sent throughout the semester as necessary:

• Piazza - a forum site where students are free to ask any questions related to homework, topics, or course logistics. You will receive a link to sign up the first week of classes. Please use this first to ask questions outside of lecture/office hours, but if you have a particularly sensitive or urgent matter, feel free to send an email to mikayla@hucs0.org.
• CSCI100 Youtube Playlist - A collection of instructional videos by previous instructor and current Google employee Alex Krenstel.
• The course website - https://hucs0.org will be your one stop shop for all information needed for this class. There, you will find lecture slides, when office hours are, staff emails, and other resources.
• Codio - This is where you will do all of your assignments in this class. You will receive a link to sign up the first week of classes. Codio will display a ‘grade’ for you, but your official grade will be in Canvas. Please reach out to your advisor if you cannot access the class on your Canvas account.