- Introduction to SAS Visual Analytics Environment
- Bar Charts in SAS Visual Analytics
- Pie Charts
- Histograms
- Step Plots
- Heat Maps
- Correlation Matrix
- Word Clouds
- Time Series in SAS Visual Analytics
- Gauge Charts
- Line Charts
- Box Plot
- Butterfly Chart
- Forecasting
- Classification
What you'll learn
- As a student you will learn how to identify and fit trends in time forecasting charts
- As a student you will be learning how to graphically validate classification machine learning models
- Once you have covered the course you will have a new background on how to visualize data in SAS Visual Analytics
- By the time you have finished this course you will have developed new trending skills on data analytics
- Part of this course is to learn how to interpret data through charts
Description
Practical SAS Visual Analytics is aimed to show examples of data visualization using SAS Visual Analytics, which is one of the leading software in the graphical analytics marketshare. To try this software requires no installation, no configuration and no previous experience. SAS Visual Analytics on SAS Viya is a cloud hosted proprietary software that requires a license to be used, since may 2019 you might be able to access it for free as an independent learner in SAS cloud servers. SAS Visual Analytics works on Linux Servers called LASR servers, it is compiled to handle massive amounts of data distributed across computer clusters. You can access to SAS VA through your web browser. The course will not have a theoretical approach to the statistical background of the charts exhibited along the videos but it it will be more a practical discussion on how-to carry out statistical charts.
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About the instructors
- 3.75 Calificación
- 8977 Estudiantes
- 1 Cursos
Joseph Adams
Machine Learning Engineer
Greetings
I am a machine learning engineer and a huge part of my career has been involved in commercial banking, insurance and retail industries. In recent years there has been a revolution in the way business are making their decisions. With the growth and the capability to store and process massive amounts of data and aided with the development of ML algorithms we have discover that strategies can be smarter if based on data.
Basically my job is to develop, assess and mantain ML models from countless source of data stored in computer clusters and then propose conclusions based on the output of the algorithm.
I hope the courses in this platform help you to find the motivation and the knowledge required to succeed in your work.
Student feedback
Course Rating
Reviews
This lecture very usefully for Visual Analytics Developer.
Concise and schematic
on n'apprend que les différentes sortes de graphiques, pas d'utilisation de SAS V.A.