In-Class Assignment: SCHOLAR Tutorial Review

All projects you will find “in the real world” require you to learn something. Knowing how to learn something new is a key learning goal of this class. To help with the many skills you may need for your project, this capstone course maintains a repository of student generated “tutorials” which can be found in the following repository:

SCHOLAR (Student-Crafted Hub for Open Learning and Academic Resources) - This is formally known as DTTD or DataTools. Please inform the instructor if there are old references still on the website.

We will be working on these during Friday classes for the rest of the semester. In today’s assignment we would like you to just review what has been done. There are three major goals for this review.

Learn how to better use git to interact with code.
Learn what content is available in this repository that may help you with your projects.
Identify ways the repository can be used to help future students.

Your team’s task for the day is to go through one of the tutorials (assigned by team by the instructors), find bugs, issue or improvement and then submit a “issue” to the git repository.

Agenda (70 Minutes)

(50 minutes) Group Review of the SCHOLAR git repository
(10 minutes) Report out to class
(10 minutes) Group co-work time

1. Group SCHOLAR Review

The following is a list of teams and the randomly assigned tutorials.

Team	Tutorial
Bradford White - Data-Driven Design	Visualizations-BERT-Topics.ipynb React Tutorial (HFH_MT).ipynb DTTD Tableau Instructions.ipynb SCHOLAR Classification.ipynb
Bradford White - Water Leak Detection	Zotero_Instructions.ipynb Uniscraper_Tutorial Mimesis.ipynb Pointers.ipynb GoogleSheetsTutorial
CEPI - Effective Communications	DataSynthesizer_Tutorial.ipynb Tidyverse_Tutorial_.ipynb environment.yml TensorFlow_Tutorial.ipynb DTTD_Tutorial_Widgets-D2LAPITeam.ipynb
Customers Lens - Entrepreneurial Challenges	PowerBI_Scholar_Workshop.md References.ipynb PTest.ipynb PySpark_Tutorial.ipynb image_thresholding_tutorial
Delta Dental - Canonical Mouth Dataset Development	Pandas.ipynb RREF.ipynb BeautifulSoup.ipynb social_media_scrapper imageassets
Henry Ford Health - Video Segmentation	Basic_Containers.ipynb polars HPCC_Initial_Tutorial.ipynb SAHI_Tutorial_COCO_Demo.ipynb lib
Joyntly - User Engagement	GAMA_AutoML_Tutorial.ipynb Matplotlib_tutorial.ipynb ssh_key_gen makefile _Template.ipynb
Kellanova - Demand Forecasting	pcatutorial.ipynb MorphologicalOperators_Tutorial faker.ipynb FineTune-Mistral-LLM-OwnData AudioDataTutorial.ipynb
Luce - Lumber	tpot_tutorial.ipynb FuzzyWuzzy.ipynb Whitespace_Indentation.ipynb Gradients.ipynb BigO_C++.ipynb
MSU - Curriculum Analytics	Selenium_tutorial.ipynb datasets gis topic-modelling tpot_environment.yml
MSU - Southwest Lansing Project	Video-Image-Data-Tutorial Orange_tutorial.ipynb BERT_VectorSimilarity_Python Loops.ipynb SCHOLAR_Google_Sheets_API.ipynb
NCEAS - Unsupervised NLP	censusdata_package_tutorial DAX_Tutorial Camtasia Seaborn_Tutorial_DTTD.ipynb SAHI_tutorial1_1.ipynb
TeliAI - Agentic Campaign Insight Analyzer	Auto_Cropping_Image_Tutorial Tidyverse_Tutorial.ipynb Auto-SKLearn_AutoML Central_Limit_Theorem.ipynb Dask_Tutorial.ipynb
ToolsForHumanity - IRIS Recognition	FFmpegDemo.ipynb Numpy_Sympy.ipynb YOLO_Tutorial GridSearchCV_Tutorial.ipynb BFG_Tutorial_DTTD.ipynb
UofM - Civil Rights Litigation Website	Eigenvalues.ipynb OpenCV_tutorial_SCHOLAR.ipynb DTTD_PowerBI_Tutorial.ipynb Streamlit Create_a_python_package.ipynb
WBPD - Crash Safety	answercheck.py GUI_Tutorial.ipynb AnomalyAndOutlierDetection.ipynb R_Shiny_App_Tutorial Networkx and Pyvis.ipynb

Your group is expected to review all of the tutorials. However, today we will start with just this small set (I recommend one tutorial per person). As a group do the following:

Clone the SCHOLAR repository.
Follow the directions and get your tutorials “working”.
Add “issues” to the git issue list for all things that need to be improved in the tutorial. Make sure the issue is well written and clearly states the file/tutorial that needs fixing. Every student should add at least one issue for that person to get credit.

Notes for making Git Issues

Gitlab and github have a simple mechanism for reporting “issues” inside the repository. Go to the SCHOLAR gitlab page and click on the “issues” button at the top. Once there you can read through the current issues and make new ones by pressing the green “new issues” button on the top right. When creating the issue put in a lot of details, be very specific about what file has the problem and what you know needs to be done to fix it. Please consider the following when submitting an issue:

Do NOT make the issue confidential. Make sure everyone in the class can see your issue.
Bad issues are things like “this is confusing” or “needs more”.
Make sure you specify the exact files and location in the file that need changing.
Feel free to suggest a change.

Getting Credit for this assignment

Each member of the team should author at least one NEW git issue (comments to existing issues do not count). More is better but help each other out and try to make good quality issues that have substance and are not redundant and/or just filler. There is always something that is missing or needs improvement.

NOTE: I realize we are using a lot of jargon. This is normal when you start a new job. Please research anything you don’t understand and talk with your team. Come to your instructor with questions if you can’t figure out something together.

Written by Dr. Dirk Colbry, Michigan State University
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.