Intermediate Data Programming

University of Washington, Winter 2024

Kevin Lin

he/him

kevinl@cs.uw.edu

Office Hours

Wednesdays and Fridays 4:30 PM–5:30 PM

Schedule a meeting

The world has become data-driven. Domain scientists and industry increasingly rely on data analysis to drive innovation and discovery; this reliance on data is not only restricted to science or business, but also is crucial to those in government, public policy, and those wanting to be informed citizens. As the size of data continues to grow, everyone will need to use powerful tools to work with that data.

In this course, students will learn:

1. More advanced programming concepts including how to compose programs with multiple modules.
2. How to work with different types of data: tabular data, text data, image data, geospatial data, etc.
3. Data science tools and libraries including Jupyter Notebook, scikit-image, scikit-learn, and Pandas.
4. Software engineering skills including asymptotic analysis, data settings, and data ethics.

This course is designed to support students who have completed:

CSE 160: Data Programming

Know control structures, file I/O, and data structures in Python. Your first weeks will be a review.

CSE 122: Introduction to Computer Programming II

Know control structures, file I/O, and data structures in Java. Your first weeks will focus on learning these concepts in Python.

What will you learn?

All the coursework is designed for our UW-IT JupyterHub. However, course materials are also publicly available should you choose to work outside of JupyterHub.

Python

Pandas

Software Engineering

Applications

Project

Why should we learn?

The education you receive in this course can help prepare you for programming jobs, but this isn’t the only purpose for computing education.¹ Education is not only about yourself and your personal gain, but also about all of us and our capacity to live together as a community.

The University of Washington acknowledges the Coast Salish peoples of this land, the land which touches the shared waters of all tribes and bands within the Duwamish, Puyallup, Suquamish, Tulalip and Muckleshoot nations. Among the traditions of the Coast Salish peoples is a value for the connectedness between all living things and a recognition of the unique ways that each of us comes to know something.²

Modern education has the idea that we all need to know the same thing. At the end of the lesson, everyone will know the same thing. That’s why we have tests, that’s why we have quizzes, that’s why we have homework: to ensure we all know the same thing. And that’s powerful—that’s important—within a certain context.

But for native culture, the idea that each listener divines or finds their own answer, their own meaning, their own teaching from the story is equally powerful—that each person needs to be able to look at the world and define it for themselves within their culture and then also find a way to live in that world according to the teachings of their people in their culture.

Our course emphasizes the following values.

We are responsible for each others’ success

Everyone has a right to feel like they belong in this course. We’ll need to act with compassion and caring to collaborate with each other. Although we will need more than just unexamined commitments to collaboration, listening, empathy, mindfulness, and caring,³ the following guidelines offer a starting point for ensuring compassion toward each other.⁴

• Listen with intention to understand first and form an opinion only after you fully understand.
• Take responsibility for the intended and unintended effects of your words and actions on others.
• Mindfully respond to others’ ideas by acknowledging the unique value of each contribution.

You should expect and demand to be treated by your classmates and teachers with respect. If any incident occurs that challenges this commitment to a supportive, diverse, inclusive, and equitable environment, please let the instructor know so the issue can be addressed. Should you feel uncomfortable bringing up an issue with the instructor directly, meet our advisors during quick questions or contact the College of Engineering.

We recognize everyone has unique circumstances

Do not hesitate to contact the instructor by private discussion post or appointment. The sooner we are made aware of your circumstances, the more we can help. Extenuating circumstances include work-school balance, familial responsibilities, religious observations, military duties, unexpected travel, or anything else beyond your control that may negatively impact your performance in the class.

It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law. If you have already established accommodations with Disability Resources for Students (DRS), activate your accommodations via myDRS so we can discuss how they will be implemented in this course. If you have a temporary health condition or permanent disability that requires accommodations, contact DRS directly to set up an Access Plan.

Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.

We believe everyone wants to learn

Education is about shaping your identity as much as it is about learning things. In school, the consequences of making mistakes are relatively small. But the habits you form now—repeated over days, weeks, months, or years—determine who you will be in the future. Now is the best time to practice honest habits.

We ask that you do not claim to be responsible for work that is not yours. When you receive substantial help from someone else, include a citation. Don’t post your solutions publicly. Most importantly, don’t deprive yourself or others of the learning opportunities that we’ve created in this course.

Academic honesty reflects the trust (or the lack thereof) between students and teachers. We do our best to design the course in ways that ensure trust, but we know our systems are not perfect. If you submit work in violation of these policies but bring it to the attention of the instructor within 72 hours, you may resubmit your own work without further consequence. Rather than blame students, we want to fix or replace broken systems that compel students to lose trust.

How will you learn?

In a traditional classroom, you attend class while a teacher lectures until time is up. Then, you go home and do the important work of applying concepts toward practice problems or assignments on your own. Finally, you take an exam to show what you know.

Today, we know that there are more effective ways to learn science, engineering, and mathematics.⁵ Learning skills like software engineering and algorithm analysis requires deliberate practice: a learning cycle that starts with sustained motivation, then presents tasks that build on prior knowledge, and concludes with immediate, personalized feedback. Each module in the course will involve several different activities that are designed so that we can make the most of our class time together.

Before lecture, skim the class activities and ask questions in the discussion board.

Optionally, in Ed Discussion, write your questions in the weekly discussion thread.

During lecture, learn and support each other on the in-class guided coding practice.

In PollEverywhere, submit your responses to complete the coding polls and activities.

In section on Thursday, work with your team to get started on the upcoming weekly programming assessment. Complete the assessment by the following week’s section for code review.

During quiz section, participate in a small-group peer code review evaluated by your TA.

In Canvas, use your browser’s PDF printer to submit your notebook as a PDF for TA review.

In Canvas early the next week, respond to your TA review questions to complete the review.

Code review discussions are the primary means of standardized assessment in this course. Rather than treat your submitted program code as the final artifact for evaluation, it is instead a starting point for a conversation that demonstrates your programming fluencies such as code writing, code reading, code debugging, and code communication skills. Communicating your ideas and explaining your decision-making is important in this course. But we know that live discussions during class may not be accessible for everyone and we would be happy to work with you to design accommodations that would allow you to communicate your programming fluencies in an accessible format for you.

The purpose of all these activities are for you to learn the course concepts, not to prove that you already know them. Working with a team and discussing problem solving approaches is an effective way to learn. You can expect to receive substantial assistance from other students and the course staff before, during, and after class. Regardless of how much help you receive from others, in order to conduct a successful code review discussion, you’ll need to be deeply familiar with all the code that you write. Do not deprive yourself or others of learning opportunities in this course.

Encouraged

Discussing examples shown in class. These examples are part of the course’s learning materials.

Working with a TA to improve your understanding of a task and resolve a particular problem.

Communicating with other students without sharing code or exact details to reproduce a solution.

Permitted with caution

Working alongside one or more other people on an assessment. Peer code review relies on students preparing sufficiently different programs that are then compared against each other.

Sharing or generating small snippets of assessment code that you did not write yourself. Code reviews require you to explain, discuss, and compare ideas about code that you wrote.

Prohibited

Obtaining or generating solutions to any significant portion of an assessment in any form.

Giving, receiving, or generating a walkthrough to an assessment from anyone or anything else.

Posting solutions to an assessment in a public place even after the course is over.

Expect to spend 4 hours in class and 8 hours outside of class working on this course. Some weeks may require more or less time than other weeks. If you find the workload is significantly exceeding this expectation, talk to your TA.

How is this course graded?

Grading in this course emphasizes both quantity and quality of coursework received for formal evaluation. Quantity is tracked primarily through completion of Canvas module requirements, while quality ratings are tracked primarily through the Canvas learning mastery gradebook.

1.0 or greater

Completion of Python and Pandas modules.

2.0 or greater

Completion of Python, Pandas, and Software Engineering modules.

3.0 or greater

Completion of Python, Pandas, Software Engineering, and Applications modules.

Satisfactory or trending toward satisfactory for all learning outcomes with at least 3 alignments each.

4.0

Completion of Python, Pandas, Software Engineering, and Applications modules.

Highest marks in Project module.

Exemplary or trending toward exemplary for all learning outcomes with at least 3 alignments each.

Grading in this course is intended to emphasize learning, and learning involves growing from the past to the present. This course supports learning by using an outcomes-based grading system that deliberately incorporates your improvement over the course of the quarter by evaluating the quality of your work as a trend over time. The Canvas learning mastery gradebook focuses on counting satisfactory ratings: after 3 satisfactory alignments have been received for a particular outcome, it will display the average of the satisfactory or exemplary ratings for that outcome. This formula provided by Canvas is far from a perfect metric, so final grades will likely utilize more nuance and additional human review.

Evaluating Assessment Approaches in Intermediate Data Programming

You are being asked to participate in a research study to find out more about how assessment approaches affect the student experience in an undergraduate data programming courses. You have been asked to participate in this study because you are a student in a class that is being studied or used as a control. The purpose of this study is to create knowledge that has the potential to improve the educational experience for students at the University of Washington and beyond.

What will you be asked to do?

Your data from this class including surveys/evaluations, coursework, and course forum discussions may be analyzed. Your participation involves only agreeing to let us use your data in our analysis. You will not be required to do anything beyond normal educational practice.

There may be additional optional opportunities to participate in follow-up interviews or focus group discussions. These are not required, and details will be provided when they arise.

What will happen to the information you provide?

Data from participants will be retained only for research purposes and stored using codes that provide a degree of confidentiality. Your instructor will not know whether you are participating in this study until after final grades have been posted.

What can you do if you want more information?

Talk to the study team. Kevin Lin is the lead researcher at the University of Washington for this study and can be contacted at kevinl@cs.uw.edu.

Talk to someone else. If you want to talk with someone who is not part of the study team about the study, your rights as a research subject, or to report problems or complaints about the study, contact the UW Human Subjects Division at hsdinfo@uw.edu or 206-543-0098.

What are my options to participate?

By default, you will be included in this study. No additional actions are required to participate.

Participation in this research, however, is optional. You may withdraw at any time without penalty by contacting Suhas Kannam at ksuhas16@uw.edu.

Explore CSE 163

• Staff - All the teaching and learning assistants.
• Style Guide - Python style conventions for this course.