: Building a custom Python package to store and reuse automation functions. Key Learning Outcomes End-to-End Workflow
: Filtering, grouping, and joining data using the Pandas library . DS4B 101-P- Python for Data Science Automation
Secondly, the course prioritizes . An automated script is useless if it requires a human to click "Run." DS4B 101-P introduces learners to scheduling, logging, and error handling. Students learn to use tools like prefect or airflow (contextually) to build Directed Acyclic Graphs (DAGs) that extract data from APIs, transform it, and load it into a database or dashboard—all while sending alerts if a step fails. This transforms Python from a calculator into a resilient, 24/7 data worker. : Building a custom Python package to store
to execute notebook-based reports on demand or on a schedule. Visualization : Crafting high-quality, report-ready charts with Business Science University Target Audience This course is specifically crafted for: Business Intelligence (BI) Professionals An automated script is useless if it requires