: Teaches how to generate executive-level deliverables. Key tools include for customizable visualizations and for automating Jupyter Notebook reports. Business Science University Skills & Tools Mastered
The curriculum is streamlined into three primary steps designed for rapid skill acquisition: DS4B 101-P- Python for Data Science Automation
For building complex, "Grammar of Graphics" style visualizations. : Teaches how to generate executive-level deliverables
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. Secondly, the course prioritizes
You have the script; now you need the robot to run it. This module covers three levels of scheduling:
But does it live up to the hype? Below, we break down everything you need to know about DS4B 101-P, its curriculum, who it is for, and why "Automation" is the secret weapon your resume is missing.
By the end of the DS4B 101-P course, students will be able to: