There is significant and growing demand for data-savvy professionals in businesses, public agencies, and nonprofits. The supply of professionals who can work effectively with data at scale is limited, and is reflected by rapidly rising salaries for data engineers, data scientists, statisticians, and data analysts. The data scientist role has been described as “part analyst, part artist," “A data scientist is somebody who is inquisitive, who can stare at data and spot trends. It's almost like a Renaissance individual who really wants to learn and bring change to an organisation."
This course helps the attendees on the road to acquiring these data science skills and goes in-depth into the methodologies and tooling all illustrated by examples. Attendees will leave with a understanding, appreciation of the Data Scientist role, their tasks and how to begin to recognise patterns and insight from their data.
- Data Science Methodology - Machine Learning Methods - Text Analytics Concepts - Continuous Streaming Analytics - Classification - Recommendation Systems - How to use Spark with SPSS Modeler - Data Science Future - How to build Data Science teams