Required One-on-One Meeting: Each student is required to meet with the instructor at least once during the semester for a brief individual check-in. This meeting is an opportunity to discuss your project progress, ask questions, and receive personalized feedback. You may schedule this meeting during office hours or by appointment.
This course teaches you to think computationally and build with judgment in the AI era.
You will learn Python not as a syntax manual to memorize, but as a practical tool to solve problems and work with data. The focus is on understanding how code works, reading and evaluating solutions (yours and AI’s), designing effective approaches, and communicating technical concepts clearly.
In 2026, the valuable skill isn’t writing code from scratch faster than AI. It’s:
This course prepares you for a world where AI writes code, but humans make decisions.
By the end of this course, students will be able to:
Students should have a basic understanding of operating a personal computer, including proficiency in using web browsers and the ability to navigate and manipulate files. Additionally, students should be familiar with opening a command prompt or terminal window, editing text files, downloading and installing software. While a basic understanding of programming concepts is preferred, it is not required.
This course does not require the purchase of a textbook. The primary learning materials will consist of Think Python 3 supplemented with the instructor’s own resources. All materials will be provided in PDF, HTML, Markdown, or Jupyter Notebook format via Canvas and/or GitHub. Students may use additional references for further study. Prior programming experience is not required.
Please install the following before the first class:
Detailed installation instructions are provided in the “Course Software” section on Canvas.
| Component | Weight | Description |
|---|---|---|
| Checkpoints | 40% | Exercises, learning logs, mini projects, etc. |
| Understanding Assessment | 20% | Paper quizzes and in-person interviews |
| Final Project | 25% | Public repo, peer review |
| Participation | 15% | In-class activities, office hours, learning log quality, etc. |
| Bonus | up to 3% | Exceptional contributions beyond requirements |
| Grade | Range |
|---|---|
| A | 94-100 |
| A- | 90-93.99 |
| B+ | 87-89.99 |
| B | 84-86.99 |
| B- | 80-83.99 |
| C+ | 77-79.99 |
| C | 74-76.99 |
| C- | 70-73.99 |
| D | 60-69.99 |
| F | 0-59.99 |
This course embraces the “Learn in Public” philosophy. You will create public repositories on GitHub for your coursework and projects. This approach:
Repository Structure:
oim3640/ # Main course repository (public)
├── notebooks/ # Jupyter notebooks (from Think Python 3)
├── code/ # Python scripts and modules
├── data/ # Data files
├── logs/ # Learning logs (Markdown files: s01.md, s02.md, ...)
├── mini_projects/ # Mini projects (may be here or separate repos)
└── README.md # Portfolio homepage
Important: You must frequently commit and push changes. All coursework is evaluated based on your repository content and commit history, which demonstrates your learning journey and iterative improvement.
Your learning progress is tracked through at least 6 checkpoints distributed throughout the semester. Checkpoints are not announced in advance; they occur naturally as part of the course flow.
Each checkpoint may include:
The goal is to assess your ongoing learning rather than performance on specific deadlines.
After each class session, submit a brief learning log in Markdown format in your logs/ folder.
File naming: s01.md, s02.md, etc.
Suggested format (use as reference, develop your own style):
# Session X (Date) - [Topic]
## What I learned today
[Brief reflection on key concepts; focus on understanding, not just syntax]
## Code/work I'm proud of (optional)
[Paste a snippet and explain what it does]
## Challenges I faced
[What was difficult? How did I approach it?]
## AI usage (if any)
[What I asked AI for, how I used/modified the output]
## Questions for next time
[What remains unclear?]
Note: Your logs are for your learning first, grading second. Write honestly about struggles and questions. This demonstrates growth mindset.
Evaluation:
Mini projects are focused explorations that demonstrate your understanding through building. They replace traditional homework assignments.
Each mini project:
Mini projects typically include:
Detailed specifications, requirements, and due dates for each mini project will be provided on Canvas and GitHub.
Your understanding is assessed through two complementary methods:
Several in-class paper quizzes throughout the semester. These are judgment-focused, not syntax-focused.
Format: Paper-based, no electronic devices
Question Types:
Philosophy: Quizzes test your ability to think about code, not memorize syntax. You should be able to:
Policy:
Specific quiz dates will be announced on Canvas and in the course schedule.
Brief conversations during checkpoint reviews where I ask you questions about your code and projects. This gives you an opportunity to demonstrate your understanding verbally and allows me to assess your learning in a more natural, conversational setting.
These interviews:
You will create an independent project that demonstrates your programming and problem-solving skills. This is your main deliverable for the course and an important part of your portfolio.
Requirements:
Evaluation Criteria:
Detailed project specifications, requirements, timeline, and due dates will be provided separately on Canvas and GitHub.
Participation is evaluated based on:
You can earn bonus points through exceptional work that goes significantly beyond course requirements:
It is mandatory for students to inform the instructor if they will be absent from a class. Students who miss a class are responsible for obtaining all materials and information that were distributed or covered during the class they missed. You are still required to complete in-class exercises and submit learning logs.
Babson College is committed to providing equal educational opportunities for students with disabilities. Any student who may need accommodation(s) based on the impact of a disability should contact the Department of Accessibility Services (DAS) as early in the semester as possible. Accessibility Services staff may be reached by email at accessibility@babson.edu, by phone at 781-239-5509, or by visiting Hollister Hall, Suite 220. Accessibility Services staff will coordinate reasonable academic accommodations for eligible students.
Any student who faces a conflict between the requirements of a course and the observance of their religious belief should contact the instructor early in the semester. In such an event, reasonable accommodations will be provided to the extent they do not create an unreasonable burden on the College.
Integrity is a core institutional value at Babson. The Babson College Undergraduate Honor Code sets forth clear expectations with regard to how your behaviors, actions, and decision making support our institutional commitment to integrity. The Code, and all that it comprises, aims to build a Community of Honor at Babson - one that is connected and strengthened by each member’s individual commitment to integrity and ethical decision making in all that we do. As a Babson student, you are committing to being an active and engaged participant in our Community of Honor, in partnership with your fellow students, faculty, staff, and alumni.
AI tools are encouraged and expected in this course. This includes ChatGPT, Claude, GitHub Copilot, and other AI assistants.
Guidelines for Responsible AI Use:
Use AI freely for learning: Ask AI to explain concepts, generate practice problems, review your code, suggest improvements
Always understand what you submit: You should be able to explain the purpose and behavior of any code in your project. Quizzes will verify your actual understanding.
Document AI assistance when required: Specific requirements for documenting AI usage will be provided with each assignment. This may include comments in code, separate documentation files, or reflection in learning logs.
Remember: AI helps you build faster, but understanding helps you build better. The goal is learning, not just getting code that runs.
In this course, you are required to abide by the College’s Academic Integrity Policies and Procedures as outlined in Babson’s Student Code of Ethics. Please review the College’s Student Code of Ethics in its entirety, as it is your responsibility to take the appropriate steps to ensure your understanding of the Code. Ignorance of the policies is not a valid excuse for any violations.
Academic integrity is important for two reasons. First, independent and original scholarship ensures that students derive the most they can from their educational experience and the pursuit of knowledge. Second, academic misconduct violates the most fundamental values of an intellectual community and diminishes the achievements of the entire college community. Accordingly, Babson views academic misconduct as one of the most serious violations of the College’s expectations that a student can commit while at Babson College. Specific behaviors that constitute academic misconduct, as defined in the Code, are cheating, fabrication, facilitating academic dishonesty, plagiarism, participation in academically dishonest activities, and unauthorized collaboration.
In this course specifically:
If I am presented with evidence to suggest that you engaged in academic misconduct, I will refer the incident to the Office of Community Standards for review.
For your coursework, you may be asked to affirm your understanding of and commitment to the academic honesty and integrity expectations set forth in the Code by writing the following pledge:
“I have abided by the Babson Code of Ethics in this work and pledge to be better than that which would compromise my integrity.”
If you have questions relative to academic integrity expectations within the context of a particular assignment, please ask me directly. General questions can be directed to communitystandards@babson.edu.
Conflict – especially when working in groups – is a normal, healthy, and expected part of life and ideally is viewed as an opportunity to strengthen relationships, improve efficiency, and rectify underlying concerns that often otherwise go unaddressed. Resolving conflict is a vital part of the educational journey of the Babson student and entrepreneur and requires your active participation and skill development. If you experience interpersonal conflict in this course, I encourage you to explore the College’s Conflict Navigation Services as a resource.
Updated: 1/16/2026