|CS 251: Data Analysis and Visualization|
An introduction to the analysis and visualization of scientific data. Topics include data management, basic statistical analysis, data mining techniques, and fundamental concepts of machine learning. Students also learn how to visualize different types of data, focusing on discovering patterns and relationships. Through programming projects, students gain hands-on experience analyzing and selecting appropriate visualizations for real datasets.
|CS 252: Mathematical Data Analysis and Visualization|
Emphasis is placed on the mathematical basis of algorithms, which are then applied to real datasets. As time allows, additional techniques involving linear algebra and calculus are covered.
|Times & Locations||
|Lab instructor||Hannah Wolfe
Email: firstname.lastname@example.org Office hours:
M 8:00-9:30am REMOTE
M 3:00-5:00pm by Appointment (remote or in-person)
W 8:00-9:30am REMOTE
more information and links
Office: Davis 114
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 over Zoom in the evenings (link posted on Google Classroom). 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!
Morning TA hours for remote students are in bold font.
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:
Projects are assigned in lab on Tuesday, Wednesday, or Thursday. There are two types of deadlines:
Projects are assigned in lab. There are two types of project submissions:
Weekly drafts are due on the same day of the week as final project submissions. To help account for differences in lab timing, your due date depends on whether you are in CS 251 or CS 252:
|Project Late Policy||
Projects are an important part of the learning experience in this course. I 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 me 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
There will be a 10-15 minute quiz most Fridays. The quizzes let you show me what you have learned. These should be quick and straightforward if you participate in lecture and review lecture notes.
In-person sections: In class
I 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 me immediately in the event of illness and other unforeseen circumstances, we will work out accommodations.
|Short weekly assignments
(CS 251 only)
Work out practice problems on worksheets or homework. Graded in a binary fashion:
You are expected to attend every class. If you must miss a class for any reason, you must email me 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. contribution.
There will be a final exam on Sunday May 16th at 9:00am for CS252 and 6:00pm for CS251 (all three sections). You must be present at the exam, there are no make-ups.
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),
I must be able to get another copy from you. I suggest you use at least the college's
personal server (
|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.
|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 ...
I am 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 me 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:
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.