CS 251/2 Labs (Spring 2026)

Description Grades Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 9 Week 10 Week 11 Week 12 Week 13 Week 14

Description	Lab objectives Gain practical experience implementing data analysis and visualization techniques discussed in lecture before starting the project. Create an intuition for what the results of different algorithms and visualization techniques will produce. Find and apply python library documentation. Use jupyter notebook and matplotlib to visualize datasets and algorithms. Use numpy, scipy, pandas, and scikit-learn to modify and analyze datasets.
Grading Policies	How labs are graded Labs contribute 5% toward your course grade in CS251 and CS252. Each lab is graded separately from projects, out of 2 points: Attendance point: Your attendance in lab is required and will contribute 1 point. You are allowed to be absent for 2 labs (excused or unexcused) with no penalty. Lab completion point: Your submitted lab work will contribute up to 1 point. Here is the grading rubric: Strong: Lab is complete. (1 pt) Developing: At least half of the lab is completed. (0.6 pt) Insufficient: The lab was not submitted or less than half completed. (0 pt) You may lose points if you do not turn in labs and projects in the expected format. There is an entry for following the submission format in the project grading rubrics. Submission format Please see Lab and project submission format. Lab due dates Your lab should be turned in by Friday night at 11:59pm. Labs received within 1 week of the due date will lower that week's lab assignment's grade by 0.4 pts. Labs will not be accepted after 1 week of the due date.
Week 1	Python and coding categorical data Due: Friday, February 6th Lab 01A Next Steps Get started on CS251/2 Project 1.
Week 2	Introduction to Jupyter, NumPy, and Matplotlib Due: Friday, February 13th Typically lab instructions will be given to you through a Jupyter notebook that should be completed and turned in. Let's start that process this week. Note: This requires that you have Jupyter installed on your computer. If you followed the CS251 software installation instructions, you should be ready to go. Otherwise, follow the instructions to install Jupyter. Download Lab 01B zipfile and move it to where you store CS251 labs on your computer. Open Terminal and `cd` your way to the Lab01b directory. Type `jupyter notebook` in the Terminal then hit enter to run the command. If that doesn't work try `python3 -m notebook` Your default web browser should launch and open a page that shows the files listed within your Lab01b directory. Open the file named `Lab01b.ipynb` and start the lab. If you have problems, please ask. Now is the time to debug the process! Please upload your completed work in the Lab01b folder on Google Classroom as a ZIP file like last week and follow the lab and project submission format. Download the matplotlib tutorial: matplotlib_tutorial_starter.ipynb.
Week 3	CS251: Logical Indexing and Categorical Data Analysis Due: Friday, February 20th Lab 02 zipfile Please upload your completed notebook on Google Classroom in a ZIP file like last week and follow the lab and project submission format. CS252: Linear Regression Due: Friday, February 20th Lab 02a zipfile Please upload your completed notebook on Google Classroom in a ZIP file like last week and follow the lab and project submission format.
Week 4	CS251: Linear Regression Due: Friday, February 27th Lab 03a zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: Polynomial Regression Due: Friday, February 27th Lab 02b zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 5	CS251: Polynomial Regression Due: Friday, March 6th Lab 03b zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: Matrix Condition Number Due: Friday, March 6th Lab 02c zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 6	CS251: K-means clustering Due: Friday, March 13th Lab 04 zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: K-means clustering and Logical Indexing Due: Friday, March 13th Lab 03 zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 7	CS251: Pandas and Data Transformations Due: Friday, March 20th Lab 05a zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: Pandas and Data Transformations Due: Friday, March 20th Lab 04a zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 8	No lab
Week 9	CS251: Principal Component Analysis Due: Friday, April 3rd Lab05b.zip Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: Principal Component Analysis Due: Friday, April 3rd Lab04b.zip Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 10	CS251: Principal Component Analysis and Images Due: Friday, April 10th Lab 05c zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: Principal Component Analysis and Images Due: Friday, April 10th Lab 04c zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 11	CS251: K-Nearest Neighbor Classification Due: Friday, April 17th Lab 06a zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: Singular Value Decomposition Due: Friday, April 17th Lab 05 zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 12	CS251: Naive Bayes and KNN Due: Friday, April 24th Lab 06b zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: K-Nearest Neighbor Classification Due: Friday, April 24th Lab 06a zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 13	CS251: Neural Networks Due: SATURDAY May 2nd Lab 07 zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions). CS252: Support Vector Machines Due: SATURDAY May 2nd Lab 06b zipfile Please upload your lab .ipynb file in a ZIP file (following the usual conventions).
Week 14	No new lab