Semester Spring 2022
Times & Locations
Section
CS 251 MWF 9:00am - 9:50am Lovejoy 215
CS 251 L A M 1:00pm - 2:20pm Davis 122
CS 251 L B M 2:30pm - 3:50pm Davis 122
CS 252 MWF 10:00am - 10:50am Davis 102
Instructors
Stephanie R. Taylor Amanda Stent
Email: stephanie.taylor@colby.edu Email: ajstent@colby.edu
Sections: CS 251 Sections: CS 252
We are available to help outside of class time, please do not hesitate to come to office hours or send us an email. We try our best to get back to you within the day. Not only do we enjoy talking about computer science, we want to get to know you!
Office hours (in person):
  M 4-5pm
  T 1-2pm
  W 8:30-10pm
  R 12-2pm
Note: I often need to change my office hours to
   accommodate meetings.
Check the image of my calendar
 each week for updates.
Remote via Zoom
(Link on Google Classroom)
Office hours:
  M-R  11-12am
Note: I am also available by appointment, including for Zoom meetings; see my Calendly
Office: Davis 112 Office: Olin 132
Lab instructor Stephanie Taylor
Email: stephanie.taylor@colby.edu
Note: CS252 students are welcome to attend CS251 lab sessions if there is space in the room, or to get help with lab assignments by attending Amanda Stent's office hours.
Evening TAs

In order to provide as much help as possible to you as you work on assignments in this course, the CS Department has hired the following former CS251ers to work as TAs in Davis 122 in the evenings. You are strongly encouraged to take advantage of this resource. The TAs are getting paid to help you, so don't feel guilty about asking them for help!

Date (Time EST) TA Email
Monday, 4:00 - 7:00 PM Ben Raivel/td> bjraiv23@colby.edu
Monday, 7:00 - 10:00 PM Brendan Martin, Changling Li, Nicolás Hillison bfmart22@colby.edu, cli22@colby.edu, nmhill23@colby.edu
Course Goals
  1. Students understand and can write programs to efficiently store and manipulate real data.
  2. Students understand to how to select appropriate visualizations for common types of data. The visualizations are well-labeled and integrated with text describing what is shown.
  3. Students understand and can implement fundamental data analysis and machine learning algorithms.
  4. Students understand and can use machine learning techniques for prediction and knowledge discovery.
  5. Students present methods, algorithms, results, and designs in an organized and competently written manner.
Grading

There will be regular opportunities for you to practice what you have learned and to demonstrate your accomplishments.

The course grade will be determined as follows:

CS 251: Data Analysis and Visualization CS 252: Mathematical Data Analysis and Visualization
Projects 50% Hands-on opportunities to implement and explore concepts from lecture.
Assigned on average every 2 weeks.
Quizzes 20% Short weekly quizzes (given most Fridays)
Participation 10% I expect you to be an active contributor in the classroom.
Final Exam 10% An opportunity at the end of the semester to demonstrate your ability to answer questions about course material.
Short weekly assignments 10% Work out practice problems on worksheets or homework. Graded in a binary fashion.
Projects 50% Hands-on opportunities to implement and explore concepts from lecture.
Assigned on average every 2 weeks.
Quizzes 20% Short weekly quizzes (given most Fridays)
Participation 10% I expect you to be an active contributor in the classroom.
Final Exam 10% An opportunity at the end of the semester to demonstrate your ability to answer questions about course material.
Short weekly assignments 10% Work out practice problems on worksheets or homework. Graded in a binary fashion.
Projects

Projects are assigned in class. There are two types of deadlines:

Check-in submissions Final submissions

Your progress is check on designated project tasks (specifics are not graded).

Updated version of check-in submission and remaining project tasks, graded out of 30 points.

Honest attempt: possible to earn at least 26/30 on the final submission.

26/30: All tasks completed, all test code returns expected outputs.

Absent: 1 point reduction for each missing check-in on final submission.

26+: All tasks completed along with creative explorations beyond the scope of core tasks (extensions).

Your check-in and final submissions should be turned in on Google Classroom; your instructor will provide information about how.
Projects Deadlines

Check-in submissions are due on the same day of the week as final project submissions: Mondays 11:59 pm EST.

Project Late Policy

Projects are an important part of the learning experience in this course. We do not want you to get behind with the project workload. To encourage this, projects later than 1 week past the due date will not be accepted.

Late projects will not be eligible for extension credit and will be capped at a maximum of 26/30.

Please contact us immediately in the event of illness and other unforeseen circumstances, we will work out accommodations.

Freebee: On one project during the semester, you may take a freebee to submit your project 3 days later than usual (e.g. Thursday 11:59pm instead of Monday). The only advantage of doing this (rather than just turning in your project within the 1 week allowable late window) is to have your extensions graded. Prior to the deadline fill out the freebee form on your Google Classroom

Weekly quizzes

There will be a 10-15 minute quiz most Fridays. The quizzes let you show us what you have learned. These should be quick and straightforward if you participate in lecture and review lecture notes.

We understand that everyone has a bad day; the quiz with the lowest grade will be dropped

Each quiz may be made up when a prior request is made or there is a documented health issue. Please contact us immediately in the event of illness and other unforeseen circumstances, we will work out accommodations.

Short weekly assignments

Work out practice problems on worksheets or homework. Graded in a binary fashion:
  1 if serious attempt made.
  0 otherwise.

CS 251 CS 252

Given over email on Wednesdays.

Given over Google Classroom on Wednesdays.

Due Thursday 11:59pm by emailing stephanie.taylor@colby.edu.

Due Thursday 11:59pm on Google Classroom.

Class Participation

You are expected to attend every class. If you must miss a class for any reason, you must email us in advance.

For this course to be truly successful, your presence and participation is important. When you have a question, ask it. It is highly probable that one of your classmates has the same question.

Final Exam

There will be a final exam on the final exam date, TBD at the final exam time, TBD. You must be present at the exam, there are no make-ups.

Backups

It should go without saying that you should back up any files related to this course. If the code you submit to us is somehow lost (through your fault or our fault), we must be able to get another copy from you. We suggest you use at least the college's personal server (filer.colby.edu) and one other cloud-based storage service (e.g. Google Drive) to store your work in this class.

Collaboration, Academic honesty

Computer science, both academically and professionally, is a collaborative discipline. In any collaboration, however, all parties are expected to make their own contributions and to generously credit the contributions of others. In our class, therefore, collaboration on assignments is encouraged, but you as an individual are responsible for understanding all the material in the assignment and doing your own work. Always strive to do your best, give generous credit to others, start early, and seek help early from both your professors and classmates.

The following rules are intended to help you get the most out of your education and to clarify the line between honest and dishonest work. We reserve the right to ask you to verbally explain the reasoning behind any answer or code that you turn in and to modify your project grade based on your answers. It is vitally important that you turn in work that is your own. We do use automated plagiarism detection software, so please be sure to abide by these, rather minimal, rules. Reports of academic dishonesty are handled by an academic review board and a finding of academic dishonesty may result in significant sanctions. For more details on Colby's Academic Integrity policies and procedures, see colby.edu/academicintegrity.

  • If you have had a substantive discussion of any homework or programming solution with a classmate, then be sure to cite them in your write-up. If you are unsure of what constitutes "substantive", then ask us or err on the side of caution. As one rule of thumb, you may discuss your approach to solving a problem, but you must not share or look at another classmate's code or written answers to project questions.
  • You must not copy answers or code from another student either by hand or electronically. Another way to think about it is that you should communicate with one another in natural human sentences, not in lines of code from a programming language.
The Colby Affirmation

Colby College is a community dedicated to learning and committed to the growth and well-being of all its members.

As a community devoted to intellectual growth, we value academic integrity. We agree to take ownership of our academic work, to submit only work that is our own, to fully acknowledge the research and ideas of others in our work, and to abide by the instructions and regulations governing academic work established by the faculty.

As a community built on respect for ourselves, each other, and our physical environment, we recognize the diversity of people who have gathered here and that genuine inclusivity requires active, honest, and compassionate engagement with one another. We agree to respect each other, to honor community expectations, and to comply with College policies.

As a member of this community, I pledge to hold myself and others accountable to these values. More ...

Academic Accommodations

We are available to discuss academic accommodations that any student with a documented disability may require. Please note that you’ll need to provide a letter from the Dean of Studies Office documenting your approved accommodations. Please meet with your instructor to make a request for accommodations at the beginning of the semester--and at a minimum two weeks before any key due dates--so that we can work together with the College to make the appropriate arrangements for you.

Title IX Statement

Colby College prohibits and will not tolerate sexual misconduct or gender-based discrimination of any kind. Colby is legally obligated to investigate sexual misconduct (including, but not limited to, sexual assault and sexual harassment) and other specific forms of behavior that violate federal and state laws (Title IX and Title VII, and the Maine Human Rights Act). Such behavior also requires the College to fulfill certain obligations under two other federal laws, the Violence Against Women Act (VAWA) and the Jeanne Clery Disclosure of Campus Security Policy and Campus Statistics Act (Clery Act).

To learn more about what constitutes sexual misconduct or to report an incident, see: www.colby.edu/studentlife/handbook-section/f-sexualmisconduct/.

If you wish to speak confidentially about an incident of sexual misconduct, you may contact:

  • Counseling Center: 207-859-4490
  • Gender and Sexual Diversity Program: Director Emily Schusterbauer (eeschust@colby.edu/ 207-859-4093)
  • Office of Religious & Spiritual Life: 207-859-4272
    • Dean of Religious & Spiritual Life, Kurt Nelson (kdnelson@colby.edu)
    • Jewish Chaplain, Erica Asch (elsasch@colby.edu)
    • Catholic Campus Minister, Charles Demm (cademm@colby.edu)

Students should be aware that faculty members are considered "responsible employees"; as such, if you disclose an incident of sexual misconduct to a faculty member, they have an obligation to report it to Colby's Title IX Coordinator. "Disclosure" may include communication in-person, via email/phone/text, or through class assignments.

© 2021 Oliver Layton, Stephanie Taylor