For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform—by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. 

 

 

 

In this course, you will implement data science techniques in order to achieve organizational goals. You will: • Use data science principles to address business issues. • Apply the extract, transform, and load (ETL) process to prepare datasets. • Use multiple techniques to analyze data and extract valuable insights. • Design a machine learning approach to address business issues. • Train, tune, and evaluate classification models. • Train, tune, and evaluate regression and forecasting models. • Train, tune, and evaluate clustering models. • Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.