Developing reusable functions to simplify repetitive forecasting tasks. :
: Transition from writing scripts to developing reusable Python packages and libraries. Key Modules and Curriculum DS4B 101-P- Python for Data Science Automation
| Module | Title | Key Automation Topic | |--------|-------|----------------------| | 1 | Automating File & Folder Operations | pathlib , batch renaming, folder monitoring | | 2 | Data Extraction Automation | Reading multiple files, API polling, database queries | | 3 | Clean Data Pipelines | Writing reusable pandas transforms, handling missing data | | 4 | Automated Reporting I | Excel and CSV exports with formatting | | 5 | Automated Reporting II | PDF and HTML reports with templates | | 6 | Scheduling & Script Execution | Cron, Task Scheduler, schedule library | | 7 | Error Handling & Logging | Making scripts fault-tolerant and auditable | | 8 | Integration Mini-Project | Full automation pipeline + basic ML forecast output | DS4B 101-P- Python for Data Science Automation
Automation wasn’t just about saving time — it was about taking back her evenings. DS4B 101-P- Python for Data Science Automation