Python For Data Science Automation ((hot)) - Ds4b 101-p-

: Integrate advanced libraries such as sktime to predict business trends.

: Professionals looking to move beyond Excel or manual reporting by leveraging automation .

: Transition from writing scripts to developing reusable Python packages and libraries. Key Modules and Curriculum DS4B 101-P- Python for Data Science Automation

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)

: Individuals who need to understand how to deliver data-driven results that improve organizational decision-making. Why It Stands Out : Integrate advanced libraries such as sktime to

: Master the Pandas library with over five hours of in-depth training on data manipulation.

: Learning how to connect to transactional databases and apply time-series models to real-world business data. Key Modules and Curriculum Most introductory courses leave

The curriculum is streamlined into three primary steps designed for rapid skill acquisition:

: Deep dives into VS Code as a development environment, SQL database interaction (specifically SQLite), and advanced data wrangling.