SAS Factory Miner
Strategies and Concepts for Data Scientists and Business Analysts
To be effective in a competitive business environment, analytics professionals need to use descriptive, predictive, and prescriptive analytics to translate information into decisions. An effective analyst also should be able to identify the analytical tools and data structures to anticipate market trends.
In this course, you gain the skills data scientists and statistical business analysts must have to succeed in today's data-driven economy. Learn about visualizing big data, how predictive modeling can help you find hidden nuggets, the importance of experiments in business, and the kind of value you can gain from unstructured data.
This course combines scheduled, instructor-led classroom or Live Web sessions with small-group discussion, readings, and hands-on software demonstrations, for a highly engaging learning experience.
Mass-Scale Predictive Modeling Using SAS Factory Miner
This course shows how to extend the machine learning techniques of SAS Enterprise Miner into an interactive web-based environment. In the course, you build customized modeling templates to enable sharing of modeling best practices across an organization. In addition, you experiment with Bayesian networks, support vector machines, random forests, and many other machine learning techniques to gain the most insight from your data.
The self-study version of this course contains structured course notes that provide a detailed overview and exercises and that help you develop essential skills. There is also a Virtual Lab that enables you to practice what you learn in the course.
The e-learning includes the following: