Slides A
Inhoud
1. Data science Competences ................................................................................................................... 2
2. Context of analytics............................................................................................................................... 3
3. The Cross-Industry Standard Process for Data Mining (CRISP-DM) & SAS’ Sample-Explore-Modify-
Model-Assess Model (SEMMA)..................................................................................................................... 4
4. Analytics Tasks and Types of analytics .................................................................................................. 5
5. Containers, VM’s and Images (docker) ................................................................................................. 6
1
,1. Data science Competences
2
,2. Context of analytics
3
, 3. The Cross-Industry Standard Process for Data Mining (CRISP-DM) &
SAS’ Sample-Explore-Modify-Model-Assess Model (SEMMA)
4
Inhoud
1. Data science Competences ................................................................................................................... 2
2. Context of analytics............................................................................................................................... 3
3. The Cross-Industry Standard Process for Data Mining (CRISP-DM) & SAS’ Sample-Explore-Modify-
Model-Assess Model (SEMMA)..................................................................................................................... 4
4. Analytics Tasks and Types of analytics .................................................................................................. 5
5. Containers, VM’s and Images (docker) ................................................................................................. 6
1
,1. Data science Competences
2
,2. Context of analytics
3
, 3. The Cross-Industry Standard Process for Data Mining (CRISP-DM) &
SAS’ Sample-Explore-Modify-Model-Assess Model (SEMMA)
4