Semester Fall 2026
Lecture Time: MWF 10:00-10:50am
Location: Davis 117
Lab Times:
Wednes 2:30-3:50pm
Location: Davis 201

Attendance is required.

Instructors
Lecture: Oliver Layton Lab: Hannen Wolfe
Email: oliver.layton@colby.edu Email: hewolfe@colby.edu
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:
M: 1:00-2:00pm
T:  11:00-12:00pm
W: 2:00-3:00pm
R: 1:00-2:00pm
Office hours:
M: 4:00-5:00pm
T:  10:00-11:00am
W: 1:00-2:00pm
F: 4:00-5:00pm
Office: Davis 115 Office: Davis 114
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 CS251 and CS252 students 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!

Sundays TA Email
4:00 - 7:00 PM Shohruh Mirrakhimov smirra29@colby.edu
7:00 - 10:00 PM Rose Agyapong rfagya27@colby.edu
7:00 - 10:00 PM Spencer Lee sjlee27@colby.edu
Mondays TA Email
7:00 - 10:00 PM Lukas Gramss lrgram28@colby.edu
Tuesdays TA Email
4:00 - 7:00 PM Spencer Lee sjlee27@colby.edu
4:00 - 7:00 PM Truong Tuan Minh mttruo27@colby.edu
7:00 - 10:00 PM David Solano dasola27@colby.edu
7:00 - 10:00 PM Rinat Ilyussizov rilyus29@colby.edu
Wednesdays TA Email
4:00 - 7:00 PM Ariel Pan ypan27@colby.edu
7:00 - 10:00 PM Alize Warraich aswarr28@colby.edu
7:00 - 10:00 PM Glory Mahenge gamahe28@colby.edu
Thursdays TA Email
7:00 - 10:00 PM Said Castro-Solano scastr27@colby.edu
Lab TAs

The CS Department has hired the following former CS251 and CS252 students to work as TAs to help out during lab. The TAs are getting paid to help you, so don't feel guilty about asking them for help!

Wednesdays TA Email
2:30 - 3:50 PM Anthony Yeh aayeh29@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:

(Base) Projects 24% Hands-on opportunities to implement and explore concepts from lecture. Graded out of 26 points.
Assigned on average every 2 weeks.
Project Extensions (Optional) 6% Extensions are graded separately from the base projects, out of 4 points. You may submit extensions for up to 4 of 7 projects of your choice, all of which will be graded by Oliver. Submitting extensions for additional projects beyond the 4/7 that you choose will NOT be graded. Given that you are performing extensions on fewer projects, each extension point will be a little harder to earn than it would be if it you were doing them for all the projects. Also, you are submitting a 3-5 minute video explaining your extensions.
Quizzes 15% Short weekly quizzes (given most Fridays). These cover material from recent lectures.
Midterm Exam 15% A 90-minute opportunity to demonstrate your ability to answer questions about concepts, code, and implementation.
Final Exam 15% A 90-minute opportunity at the end of the semester to demonstrate your ability to answer questions about concepts, code, and implementation. Will be cumulative.
Homework 5% Work through practice problems. Graded in a binary fashion, assigned in preparation for each quiz.
Attendance 5% I expect you to attend every lecture, unless you are sick or must be absent for unavoidable reasons. In either case, please let me know in advance.
Participation 5% I expect you to be an active contributor in the classroom and/or during office hours.
Labs 5% Labs are graded separately from projects. To earn the full score on each lab assignment, you must attend lab and turn in the lab assignment by Friday night.
Labs are assigned weekly.
Code Review Quizzes (Lab) 5% Short paper quizzes during select labs (see Lab website for schedule) testing your understanding of your most recent project. Each quiz is printed using the actual code you submitted, making your quiz unique. The quiz should be straightforward if you understand the code that you submit.
Projects and Extensions

Projects have multiple components, and, therefore, multiple deadlines:

Check-in submissions Base Project submissions Extension submissions (Optional)
Wednesday 11:59 pm EST Wednesday 11:59 pm EST Friday 11:59 pm EST

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 26 points.

Extensions (due 2 days after the final project submission deadline). Extensions will be graded for up to four projects (251) or three projects (252).

Grade appears in grade for base project.

Grade appears in grade for base project.

Grade appears in separate extension assignment.

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

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

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

Up to 4 points for creative, thorough, well-explained extensions.

Your submissions should be turned in on Google Classroom your instructor will provide information about how.
One Week 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.

The deadline for Extensions is a hard deadline - two days after the posted deadline. If you want to complete extensions, you must complete your project on time.

Because late projects come in at different times, please understand that grading and returning late projects will typically require more time compared to on-time projects.

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

Project Freebee

We are not implementing project freebees in this course because of the change to the Extensions policy. The idea behind the freebee was that you had an opportunity to submit extensions late in one project out of seven. But now, you will be completing extensions for at most four projects (251) or three projects (252). This means you can choose to complete extensions on projects during weeks where you do not have an unusually high workload.

AI

Effective use of AI has become a core skill in modern computer science and related fields. We encourage you to use AI in this course to build your proficiency. However, with freedom comes responsibility: use AI to enhance your learning, not replace it. You must find balance in your usage so that you learn effectively — this looks different for everyone and requires experimentation.

A primary goal of this course is to prepare you as a tool builder. That requires hands-on practice with coding, design, and analysis. If AI does that heavy lifting for you, you have gone too far. Here are a few ideas to guide your AI usage:

  • Code review: Write a method yourself, then have AI help you check your work. Make sure you understand any suggestions or fixes the AI proposes. Never accept fixes blindly; your solution may be better aligned with the project goals.
  • Explore alternative implementations: Ask AI for more readable or efficient implementations. You might learn about an approach that you did not consider!
  • Mock quizzes: Have AI quiz you on concepts, code, or results.

Ultimately, you are responsible for all the code and analyses that you turn in; AI cannot take the blame for shortcomings. Here are several points to keep in mind:

  • For base projects, you should only use Python packages listed in Software. Do not let AI convince you otherwise.
  • Be cautious of AI suggestions that involve esoteric or exotic functions or overly complex implementations. If you cannot read and understand them, do not include them!
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.

Given over Google Classroom on Monday. Due Thursday 11:59am (noon) on Google Classroom. This is a strict deadline because I post the solutions on Google Classroom after the due date.

Class Participation

You are expected to attend every class and lab. 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.

Midterm Exam

  • There will be a 90-minute evening midterm exam on Monday October 19 7-10pm. To accommodate universal access, everyone may have 3 hours to complete the exam (7:00 - 10:00pm).
  • The exam will contain questions involving course concepts and project results, coding, and implementation. There are no makeups.

Final Exam

There will be a final exam (Saturday December 19th 9am-12pm). You must be present at the exam, there are no make-ups. The exam will contain questions involving course concepts and project results, coding, and implementation.

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.

  • Start by trying to solve homework, lab and project assignments yourself. You will get out of this course what you put into it.
  • Please acknowledge any assistance you get from classmates, TAs or instructors.
  • Please cite or acknowledge any online resources you use. This includes any help from online discussion or from AI tools.
  • 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. 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. For more information about the Dean of Students Office: https://www.colby.edu/studentadvising/student-access-and-disability-services/.

Mental and Emotional Wellbeing

We are invested in the mental and emotional health of our students. Even as we establish and maintain the academic standards of our course, we value each of you as individuals with complex lives, identities, and challenges.

Throughout the semester, the responsibilities of your Colby education may interact with situational as well as ongoing mental and emotional challenges in foreseeable and unforeseeable ways. If you are in need of reasonable flexibility due to an emotional situation or an ongoing mental health issue, please communicate as openly as possible with your Class Dean, and/or members of the office of Access and Disability Services, preferably in advance of the need, so that we can discuss how your circumstances interface with course requirements. Together, we will consider what is needed and what is possible. If we can discuss the situation, we can manage the situation together.

Please do not allow academic responsibilities to prevent you from getting help you need. Our Colby Counseling Services staff (207-859-4490) and the staff in the Dean of Studies office (207-859-4560) are available to connect with you. The safety of our students and every member of this community is paramount. If you or someone you know is struggling with thoughts of suicide or may be a danger to themselves or others, please call the on-call counselor immediately (207-859-4490, press ‘0’).”

Respect for Diversity

It is our intent that students from diverse backgrounds and perspectives be well-served by this course, that students' learning needs be addressed both in and out of class, and that the diversity that students bring to this class be viewed as a resource, strength and benefit. We expect you to feel challenged and sometimes outside of your comfort zone in this course, but it is our intent to present materials and activities that are inclusive and respectful of all persons, no matter their gender, sexual orientation, disability, age, socioeconomic status, ethnicity, race, culture, perspective, and other background characteristics.

Class rosters are provided to each instructor with the student's legal name. We will gladly honor your request to address you by an alternate name and/or gender pronoun. Please advise your instructor of this early in the semester so that we may make appropriate changes to our records.

Athletic Participation

While Colby College is supportive of athletic participation by its students, academics take priority over athletics. Both NCAA and Colby rules prohibit missing class for practices. In the case of overlapping commitments between class and athletic competitions, the student must meet with the instructor as soon as possible to discuss these overlaps. The student may request permission to miss class and make up the missed work; the instructor has final authority either to grant or to withhold permission.

Religious Holidays

If we have inadvertently scheduled an exam or major deadline that creates a conflict with your religious observances, please let us know within two weeks of the start of classes so that we can make other arrangements. Colby College is supportive of the religious practices of its students, faculty, and staff. The College is committed to ensuring that all students are able to observe their religious beliefs without academic penalty.

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: https://www.colby.edu/studentlife/handbook-section/f-sexualmisconduct/.

We are committed to all Colby students feeling safe, accepted, and included in all aspects of their college experiences, including this course. Colby prohibits and will not tolerate sexual misconduct or gender based discrimination of any kind and is obligated, by federal and state laws, to respond to reports and provide resources to students. Your instructors are considered "responsible employees"; we are required to report any incidence of sexual assault, sexual harassment, dating violence, or stalking to the Title IX Coordinator.

If you wish to access confidential support services, you may contact:

  • The Counseling Center: 207-859-4490
  • The Title IX Confidential Advocate, Emily Schusterbauer: 207-859-4093
  • The Office of Religious and Spiritual Life: 207-859-4272
  • Maines's 24/7 Sexual Assault Helpline: 1-800-871-7741

© 2026 Oliver Layton, Stephanie Taylor, Hannen Wolfe