First Week Online
For the first week of the quarter, all CSE 163 meetings will be held online. This includes class sessions, quiz sections, and office hours. We will have information soon on how to attend these sessions which will be hosted on Zoom.
This is a very preliminary version of our course website to get this information out there. We will have more details about the course and how it will operate soon.
Welcome to CSE 163: Intermediate Data Programming! 🎉
What is this class? What will I learn?
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.
This course teaches intermediate data programming. It is a follow on to CSE142 (Computer programming I) or CSE160 (Data Programming).
The course complements CSE143, which focuses more deeply on fundamental programming concepts and the internals of data structures. In contrast, CSE163 emphasizes the efficient use of those concepts for data programming.
In this course, students will learn:
- More advanced programming concepts than in CSE142 or CSE160 including how to write bigger programs with multiple classes and modules.
- How to work with different types of data: tabular, text, images, geo-spatial.
- Ecosystem of data science tools including Jupyter Notebook and various data science libraries including scikit image, scikit learn, and Pandas data frames.
- Basic concepts related to code complexity, efficiency of different types of data structures, and memory management.
Prerequisites and Expectations
This is class is designed as the second introductory programming course that focuses on writing programs that work with data. The prerequisites for the class require students having taken CSE 142 or CSE 160 and the class has been designed to be accessible to students from either of those backgrounds. Students that have taken 143 are welcome to take this class as it will serve as a complement to the material learned in 143 with only minor overlap.
Because this course will have students coming from many different class backgrounds, the first couple of weeks will be pretty different for students depending on what classes they have taken. Here is what we expect students to see in the first weeks based on their background:
- 142: The first two weeks might go pretty fast, but will be doable since you already know all the concepts (loops, conditionals, methods) and you are just learning all the new “words” in Python to use those concepts. This might require a little bit of extra practice early in the quarter so you are familiar with translating all the ideas you have learned in 142 to this new language. The first week has been designed to be a recap of all things 142 so you don’t also have to be learning a ton of new material while learning a new language in the first week.
- 160: The first week will just be a bit of a review for you, but the class will start covering material you haven’t seen before starting in the second week.
- 143: You are in a similar boat as the 142 students, where you know a lot of the concepts but don’t know the Python language. You’ll probably see a few things that you saw in 143 in this class, but I think the new context of processing data in a new language will still keep it new, exciting, and challenging.
If you want to learn more about the course and its policies, please check out our course syllabus.
Feedback
Feedback is always welcome! You can contact the the course staff or submit anonymous feedback.
Registration
Do not email the course staff or instructor requesting an add-code for the course. The course staff do not have any add-codes. Please email ugrad-advisor@uw.edu.
Announcements¶
Jan 25 Update: Return to mostly in-person learning next week (1/31)
Information on the return to in-person instruction next week.
See the full announcement on Ed! Jan 23 New: Grades Collected in Canvas Gradebook
Information on how to view grades in Canvas gradebook.
See the full announcement on Ed! Jan 21 End of Week 3 Announcements
- Module 2 Assessments released (Take-Home Assessment 2 and Checkpoint 2)
- New: Learning Recaps (count towards lesson completion)
- Schedule for next week
This Week (at a glance)¶
Monday - 03/07
- 📝 Checkpoint 9: Fairness and Privacy due at 11:59 pm
Tuesday - 03/08
- Project Deliverables - Code/Report due at 11:59 pm on Gradescope.
- 🔁 Weekly resubmission period closes at 11:59 pm
Wednesday - 03/09
- Project Deliverables - Video due at 11:59 pm on DevPost.
Friday - 03/11
- Project Peer Feedback due at 11:59 pm on Google Forms.
Calendar¶
For students not currently in CSE 163, you can view the Lesson material here. For students who are in the class, you can find the link to the relevant lesson below.
Info
This is a rough sketch of the quarter and things are subject to change. We can accurately predict the past, but predicting the future is hard!
Lessons
Anything listed in the “Lesson” materials for a day should be read before attending class that day. We recommend doing all the slides before the “Pause and Think” slide. Each class session will start by reviewing what was in the Lesson and then most time will be spent on working on practice problems in the Lessons. See the syllabus for more info!
Topic | Take-home assessments | Checkpoints | ||
---|---|---|---|---|
Module 0 - Python Fundamentals | ||||
Mon 01/03 | LES 00 Intro to CSE 163; Intro to Python Note: Normally you would complete the Lesson reading portion before class. There is nothing you need to complete before class today! Complete by EOD today for EC. | |||
Wed 01/05 | LES 01 Control Structures | |||
Thu 01/06 | SEC 00 Welcome to Section! | |||
Released CP0 Due 11:59 pm Intro/Review Python | ||||
Fri 01/07 | LES 02 Strings and Lists | |||
Released A0 I.S. by 11:59 pm Startup | ||||
Module 1 - Data Structures and Files | ||||
Mon 01/10 | LES 03 File Processing | |||
Wed 01/12 | LES 04 Data Structures | |||
Thu 01/13 | SEC 01 Python Practice | |||
Released CP1 Due 11:59 pm Data Structures and Files | ||||
Fri 01/14 | LES 05 CSV Data | |||
Released A1 I.S. by 11:59 pm Primer | ||||
Module 2 - Pandas | ||||
Mon 01/17 | HOLIDAY Martin Luther King Jr. Day Note: This reading is optional. Everyone will get Lesson EC for today, regardless of whether or not you do today's reading. lesson: lesson | |||
Tue 01/18 | ||||
Wed 01/19 | LES 07 pandas : DataFrame s | |||
Thu 01/20 | SEC 02 pandas | |||
Released CP2 Due 11:59 pm pandas | ||||
Fri 01/21 | LES 08 pandas : Group-by and Apply | |||
Released A2 I.S. by 11:59 pm Pokemon | ||||
Module 3 - Data Science Libraries | ||||
Mon 01/24 | LES 09 Data Visualization | |||
Wed 01/26 | LES 10 Introduction to Machine Learning | |||
Thu 01/27 | SEC 03 Data Science Libraries | |||
Released CP3 Due 11:59 pm Data Science Libraries | ||||
Fri 01/28 | LES 11 ML cont.; ML and Society | |||
Released A3 I.S. by 11:59 pm Education | ||||
Module 4 - Classes and Objects | ||||
Mon 01/31 | LES 12 Objects | |||
Wed 02/02 | LES 13 More Objects | |||
Thu 02/03 | SEC 04 Classes and Objects | |||
Released CP4 Due 11:59 pm Classes and Objects | ||||
Fri 02/04 | LES 14 Search Prep | |||
Released A4 I.S. by 11:59 pm Search | ||||
Module 5 - Efficiency | ||||
Mon 02/07 | LES 15 Algorithmic Efficiency | |||
Wed 02/09 | LES 16 Profiling and Program Speed | |||
Thu 02/10 | SEC 05 Office Hours | |||
Released CP5 Due 11:59 pm Efficiency | ||||
Fri 02/11 | LES 17 Computer Memory | |||
Released PROJ Due 11:59 pm Proposal | ||||
Module 6 - Geospatial data | ||||
Mon 02/14 | LES 18 Geospatial Data | |||
Wed 02/16 | LES 19 Dissolve and Joins | |||
Thu 02/17 | SEC 06 Geospatial Data | |||
Released CP6 Due 11:59 pm Geospatial Data | ||||
Fri 02/18 | LES 20 Indexes / Trees | |||
Released A5 I.S. by 11:59 pm Mapping | ||||
Module 7 - Special Topics | ||||
Mon 02/21 | HOLIDAY President's Day | |||
Tue 02/22 | ||||
Wed 02/23 | LES 22 Hashing | |||
Thu 02/24 | SEC 07 TA's Choice! | |||
Released CP7 Due 11:59 pm Special Topics | ||||
Fri 02/25 | LES 23 Ethics - Guest Speaker: Emily McReynolds | |||
Released PROJ Due 11:59 pm Deliverables - Report/Code | ||||
Module 8 - Images | ||||
Mon 02/28 | LES 24 numpy and Images | |||
Wed 03/02 | LES 25 Convolutions | |||
Thu 03/03 | SEC 08 Images | |||
Released CP8 Due 11:59 pm Images | ||||
Fri 03/04 | LES 26 Machine Learning and Images | |||
Module 9 - Data Science and Society | ||||
Mon 03/07 | LES 27 Algorithmic Fairness | |||
Wed 03/09 | LES 28 Algorithmic Privacy | |||
Thu 03/10 | SEC 09 Statistics and p-hacking | |||
Released CP9 Due 11:59 pm Fairness and Privacy | ||||
Fri 03/11 | LES 29 Victory Lap & Next Steps | |||
Module 10 - Finals Week | ||||
Mon 03/14 | ||||
Tue 03/15 | ||||
Released PROJ Due 11:59 pm Deliverables - Video | ||||
Wed 03/16 | ||||
Released PROJ Due 11:59 pm Peer Feedback | ||||
Thu 03/17 | ||||
Fri 03/18 | ||||