Welcome to CSE 160!

Summer 2025

Instructor: Adrian Salguero

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TAs: Kellen, Sahil, Suhas, and Tiernan

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Lecture Overview

• Introductions!
• About this Course
• Course Components & Tools
• Grading
• Policies
• Making the Most of this Class
• Introduction to Python

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Course Instructor: Adrian Salguero

• Born and raised in Los Angeles, CA
• Bachelors in Computer Science from UC Santa Cruz
• PhD in Computer Science from UC San Diego
• Research focus in Computer Science Education
• Hobbies/interests include running, weightlifting, video games, comics, and baseball

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Your Amazing Course TAs!

Kellen Rodriguez

Sahil Verma

Suhas Kannam

Tiernan Kennedy

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What is this Class?

• Python fundamentals
• Variables & Expressions
• Loops
• Lists
• Conditionals (If-statements)
• File I/O
• Dictionaries
• Nested Structures
• Data Visualization
• Python Classes and Objects
• Computational Thinking!

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Prerequisite Knowledge

• There are no prerequisites for this course!
• We do assume that you are familiar with high school math and basic computer usage (e.g. running apps, editing files, etc.)
• We assume everyone has zero prior programming experience
• If you have already taken CSE 143 or CSE 123, you cannot receive credit for this course!
• I encourage you to enroll in CSE 163 instead.
• If you already have extensive knowledge in Python or another programming language (such as Java or C), the first half of this course may be very slow and familiar.

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Lecture Overview

• Introductions!
• About this Course
• Course Components & Tools
• Grading
• Policies
• Making the Most of this Class
• Introduction to Python

7

Course Components

Lectures

• We’re here!
• Introduce concepts, practice ideas, discuss applications
• Recorded 🎥

Sections

• Held in person
• More practice, reviews, and written check-ins
• TA-led
• 🚨 Not Recorded! 🚨

Programming Assignments (HW)

• Structured assignments
• Programming in Python
• Applying & Implementing course concepts

Coding Practice

• Smaller programming questions
• Meant to give you more practice with Python fundamentals

Exams

• One midterm and one final exam

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Course Website

cs.uw.edu/160

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All course resources will be found here!

Please familiarize yourself with the syllabus and check regularly!

Course Tools

Ed

• Announcements
• Q&A

Canvas

• Recordings
• Grades

Gradescope

• Assignment submissions

Anaconda/VS Code

• Coding environment

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Lecture Overview

• Introductions!
• About this Course
• Course Components & Tools
• Grading
• Policies
• Making the Most of this Class
• Introduction to Python

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Grade Breakdown

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Exam Grading Policy

Sometimes when we take an exam, we don’t give it our best shot or we wish we could have done better. Therefore in this class has the following policy:

If your final exam score is higher than your midterm score

→ Your final exam score replaces your midterm score.

If your final exam score is lower or the same as your midterm score

→ Your midterm score remains unchanged.

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Course Grades

The following are minimum GPA guarantees - grade can always be higher than minimum promise 😊

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Lecture Overview

• Introductions!
• About this Course
• Course Components & Tools
• Grading
• Policies
• Making the Most of this Class
• Introduction to Python

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Resubmissions

Learning is a challenging process that takes time, it doesn’t always happen on your first try!

At a certain point in the course, each week you will have the opportunity to resubmit one of your previous programming assignments.

• Grade on resubmission replaces original grade
• You cannot resubmit an assignment until you receive feedback (~ 1 week)
• Accompanied by a short write up of changes made (helps your TA 😊)
• An assignment found to involve academic misconduct may not be resubmitted

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Collaboration

• Programming concepts can be challenging – we strongly encourage discussion and collaboration!
• Don’t attempt to gain credit for something you didn’t do!
• In general, share ideas and work together, but don’t copy work!
• Never show someone else your code or solutions!
• Be aware of and avoid use of Prohibited Actions in submitted work.
• Using AI-assisted tools to write code
• Looking at another person’s submission or solution
• Copying or using code copied from another resource (even with edits)
• Read full policy in the Syllabus

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Lecture Overview

• Introductions!
• About this Course
• Course Components & Tools
• Grading
• Policies
• Making the Most of this Class
• Introduction to Python

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How Learning Works

• Learning requires active participation in the process. It’s not as simple as sitting and listening to someone talk about it.
• Requires deliberate practice and learning by doing
• Benefits from collaborative learning
• Active learning during lecture
• Attendance isn’t graded but showing up will help you stay on track
• Live coding and active practice will happen during lecture

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Metacognition while Programming

• Metacognition: asking questions and thinking about your solution process and approach
• Examples:
• While debugging: explain to yourself why you’re making this change to the program, don’t “throw everything at the wall:
• Before running your program: make a prediction of what you expect to see
• When coding: if you aren’t making practice, take a break or try something approach

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Getting Help

• Discussion Board (Ed)
• Make a public or private post
• We encourage others to answer others’ questions!
• Section
• Smaller groups and face-to-face interaction with your TAs
• Office Hours
• Instructor or TA office hours! Check out the calendar on the website.
• Email
• Prefer any content and logistics questions go to Ed
• For serious or personal circumstances, please email Adrian directly.

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We Value Your Feedback!

• We are always looking for feedback on how this course can improve for you and future students!
• Let us know what is working and what isn’t working for you.
• Is there something that really worked for you in another course? Tell us!
• Post on the discussion board
• NOTE: Anonymous on Ed is anonymous to other students, not staff!
• Submit feedback via the Anonymous Feedback Tool (on website)

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Our Goal for CSE 160

• We hope to give you a great CSE 160 experience!
• We hope you’ve chosen to enroll in this course because you hope to learn and gain some value out of it.
• The course policies are designed to give you flexibility in your learning experience
• CSE 160 does not exist in a vacuum – there’s a lot going on in the world right now and in your lives that can impact your education and learning

Please reach out if you need any accommodations of any kind to deal with these unfamiliar situations! We are here to support and help you learn 😊

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Lecture Overview

• Introductions!
• About this Course
• Course Components & Tools
• Grading
• Policies
• Making the Most of this Class
• Introduction to Python

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