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 that 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.
The self-study e-learning includes:
Who should attendStatisticians, market researchers, information technology professionals, data scientists, and business analysts who want to make better use of their data
Before attending this course, you should have taken a college-level course in statistics, covering distribution analysis, hypothesis testing, and regression techniques or have equivalent knowledge. You can gain this knowledge from the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course.
This course addresses SAS Enterprise Miner, SAS Text Miner, SAS Model Manager, SAS Visual Analytics, SAS Visual Statistics software.
|Title||Duration||Access Period||Language||Fee||Add to Cart|
|Strategies and Concepts for Data Scientists and Business Analysts (15.2) (PDF + 30 virtual lab hours)||21.0 hours||180 days from order date||English||1,445 GBP|