Create complete folder structure for DP-100 Mini Projects repository

[Copilot]

This PR establishes the foundational folder structure for the DP-100 Mini Projects repository, creating all necessary directories and placeholder files as outlined in the project documentation.

Changes Made

Created the complete weekly project structure:

• Week1_BuildYourLab/ - Environment setup and workspace design

  • workspace_setup.md - Azure ML workspace configuration guide
  • conda_env.yml - Environment dependencies specification
  • sample_data/ - Directory for sample datasets (Thai rainfall, NYC taxi, etc.)
  • compute_config.json - Compute targets configuration

• Week2_SentimentExplorer/ - Data exploration and experimentation

  • automl_notebook.ipynb - AutoML experiments for Thai/English review data
  • review_data/ - Directory for Thai restaurant review datasets
  • mlflow_tracking.md - MLflow experiment tracking documentation

• Week3_SmartDeployment/ - Model training, pipelines, and deployment

  • training_script.py - Custom training scripts for school attendance prediction
  • pipeline_config.json - ML pipeline configuration
  • deployment_test.md - Online and batch endpoint deployment guide

• Week4_AskTheArchive/ - Language model optimization and RAG

  • promptflow_chain.json - Prompt flow SDK chain definitions
  • rag_config.md - RAG configuration for Thai educational documents
  • fine_tuning_script.py - Fine-tuning scripts for Thai-English datasets

All files are created as empty placeholders, ready for future content development. The structure aligns perfectly with the existing README.md documentation and supports the project-based learning approach for the Azure Data Scientist Associate certification.

Impact

This establishes the foundation for hands-on DP-100 learning modules, enabling structured development of:

• Azure ML workspace configurations
• AutoML and MLflow tracking examples
• Custom training and deployment pipelines
• RAG-based Q&A systems with Thai language support

The repository is now ready for classroom and professional development use with a clear, organized structure that matches the weekly curriculum outlined in the documentation.

This pull request was created as a result of the following prompt from Copilot chat.

Create the following document and folder structure in the repository, including empty files and folders as placeholders where content is not specified:

DP-100-Mini-Projects/
├── Week1_BuildYourLab/
│ ├── workspace_setup.md
│ ├── conda_env.yml
│ ├── sample_data/ (directory only)
│ └── compute_config.json
├── Week2_SentimentExplorer/
│ ├── automl_notebook.ipynb
│ ├── review_data/ (directory only)
│ └── mlflow_tracking.md
├── Week3_SmartDeployment/
│ ├── training_script.py
│ ├── pipeline_config.json
│ └── deployment_test.md
├── Week4_AskTheArchive/
│ ├── promptflow_chain.json
│ ├── rag_config.md
│ └── fine_tuning_script.py
└── README.md

All files should be created as empty placeholders unless otherwise specified. All directories should be created even if empty.

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