SAS Visual Statistics
| Titre | Niveau | Types de formation |
|---|---|---|
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. |
3 Intermédaire |    |
|
Data Mining Techniques: Predictive Analytics on Big Data
This course introduces applications and techniques for assaying and modeling large data. The course also presents basic and advanced modeling strategies, such as group-by processing for linear models, random forests, generalized linear models, and mixture distribution models. Students perform hands-on exploration and analyses using tools such as SAS Enterprise Miner, SAS Visual Statistics, and SAS In-Memory Statistics. |
3 Intermédaire |  |
|
SAS Visual Statistics : Construction Interactive de Modèles
Ce cours présente SAS Visual Statistics pour la construction de modèles prédictifs. SAS Visual Statistics introduit le concept d'exploration de données et de construction interactive des modèles qui sont essentiels dans le traitement et la modélisation des Big Data. |
3 Intermédaire | |