By the end of this course, you will be able to:
DS4B 101-P is an introductory-to-intermediate course designed for aspiring data scientists, analysts, and automation engineers who want to move beyond one-off scripts and manual reporting. This course teaches you how to use Python to automate repetitive data tasks, build reusable data pipelines, and integrate data science workflows into business processes.
You’ll learn how to write clean, efficient Python code that not only analyzes data but also automates the extraction, transformation, loading (ETL), reporting, and file management tasks that consume up to 80% of a data professional’s time. DS4B 101-P- Python for Data Science Automation
Before automating, you must master the fundamentals. However, unlike beginner courses that linger on "Hello World" for weeks, DS4B 101-P fast-tracks Python syntax with a focus on the tools required for automation: functions, classes, and error handling (try/except blocks). You learn to write robust code that doesn't crash when the data changes slightly.
DS4B 101-P (Python for Data Science Automation) is an online, project-based course that teaches you how to go beyond ad-hoc analysis. The core promise of the course is to teach you how to automate data science workflows using Python. By the end of this course, you will
Where most MOOCs (Massive Open Online Courses) teach you syntax (e.g., "This is a pandas dataframe"), DS4B 101-P teaches you systems (e.g., "This is a script that emails your sales team the forecast every Monday").
The course focuses heavily on the "production" side of data science—taking your messy notebook code and refactoring it into clean, repeatable, automated scripts. Before automating, you must master the fundamentals
Here is where "Business" meets "Science." You learn to automate the output of insights.
Build a complete Sales Performance Automation System: