Ds4b 101-p- Python For Data Science Automation -

: Transition from writing scripts to developing reusable Python packages and libraries. Key Modules and Curriculum

The curriculum is streamlined into three primary steps designed for rapid skill acquisition: DS4B 101-P- Python for Data Science Automation

: Deep dives into VS Code as a development environment, SQL database interaction (specifically SQLite), and advanced data wrangling. : Transition from writing scripts to developing reusable

: Integrate advanced libraries such as sktime to predict business trends. Python for Data Science Automation (Course 1) :

Most introductory courses leave students with "siloed" skills. DS4B 101-P focuses on the , ensuring that by the end of the program, you have a functional system you can deploy in a corporate environment. It is the entry point for the Business Science R-Track or Python-equivalent systems, emphasizing "full-stack" data science capabilities. Python for Data Science Automation (Course 1)

: Creating data products that provide on-demand results for executives. Who is This Course For?

: Learning how to connect to transactional databases and apply time-series models to real-world business data.