Add raw and cleaned Git classroom dataset (claude/dataset_D_git_classroom_activity.csv and _clean.csv) and two Sweetviz HTML reports. Update several lab notebooks (lab02_task1_datasets.ipynb, lab02_task1_datasets_v2b.ipynb, lab02_task2_telemetry_v4.ipynb, lab02_task3_git_activity_solutions.ipynb) and deploy/lab01_task2_telemetry.ipynb to incorporate the new data, cleanup steps, and EDA outputs.
Prepare deployment package and clean telemetry/lab data: add deploy/ (README, datasaurus.csv, datasets and lab01 notebooks), add new lab02 dataset notebook variants (lab02_task1_datasets_v2/ v2b) and solutions for task3, and update multiple lab02 telemetry and git-activity notebooks. Clean and normalize claude/dataset_A_indie_game_telemetry_clean.csv (fill/standardize timestamps, session lengths and other fields) to improve consistency for downstream analysis.
Move nbformat and metadata blocks to the end of claude/lab02_task3_git_activity.ipynb, normalize whitespace/blank lines, replace em-dash characters with ASCII double-hyphens in markdown, and add an explicit <br> for spacing. Pure formatting and markdown cleanups to keep the notebook structure consistent.
Add a comprehensive README that explains how to prepare a Python virtual environment, install packages, and register an ipykernel for running the lab notebooks in VS Code. Include two starter notebooks: TASK0_Datasaurus_Starter.ipynb (datasaurus warm-up with data loading, summary stats, optional SweetViz report, and faceted scatter plotting) and VisInt_Lab_01_Task_0.ipynb (lab header/metadata). Add .gitignore to exclude a local /.venv directory.
