Overview
Key Features
In addition, a business case study is defined to guide participants through all steps of the analytical life cycle, from problem understanding to model deployment, through data preparation, feature selection, model training and validation, and model assessment. A series of demonstrations and exercises is used to reinforce the concepts and the analytical approach to solving business problems.
This Machine Learning Using SAS Viya offered by Coursera in partnership with SAS uses Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. You learn to train supervised machine learning models to make better decisions on big data. The SAS applications used in this course make machine learning possible without programming or coding.
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Visit programme websiteProgramme Structure
Courses include:
- Getting Started with Machine Learning using SAS® Viya®
- Data Preparation and Algorithm Selection
- Decision Trees and Ensembles of Trees
- Neural Networks
- Support Vector Machines
- Model Deployment
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 1 months
- 11 hrs/week
Start dates & application deadlines
Language
Delivered
Disciplines
Computer Sciences Data Science & Big Data Machine Learning View 590 other Short Courses in Data Science & Big Data in United StatesExplore more key information
Visit programme websiteWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Intermediate Level
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved.