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Offered By

Using SAS Viya REST APIs with Python and R

SAS

About this Course

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SAS Viya is an in-memory distributed environment used to analyze big data quickly and efficiently. In this course, you’ll learn how to use the SAS Viya APIs to take control of SAS Cloud Analytic Services from a Jupyter Notebook using R or Python. You’ll learn to upload data into the cloud, analyze data, and create predictive models with SAS Viya using familiar open source functionality via the SWAT package -- the SAS Scripting Wrapper for Analytics Transfer. You’ll learn how to create both machine learning and deep learning models to tackle a variety of data sets and complex problems. And once SAS Viya has done the heavy lifting, you’ll be able to download data to the client and use native open source syntax to compare results and create graphics.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

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Approx. 18 hours to complete

English

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Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Approx. 18 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Jordan Bakerman

Analytical Training Consultant

Education

42,108 Learners

4 Courses

Ari Zitin

Analytical Training Consultant

SAS Education

3,956 Learners

2 Courses

Offered by

SAS

Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.

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Syllabus - What you will learn from this course

Week1

Week 1

1 hour to complete

Course Overview

1 hour to complete

1 video (Total 1 min), 4 readings, 1 quiz

2 hours to complete

SAS® Viya® and Open Source Integration

2 hours to complete

10 videos (Total 55 min)

10 videos

SAS Approach to Open Source Integration2mCloud Analytic Services2mJupyter Notebooks and Open Source Development Interfaces2mSAS Scripting Wrapper for Analytics Transfer2mCAS Actions in SAS Viya2mConnecting to CAS and Reading in Data1mDataFrames and CAS Tables on the Clients and Server2mAdvantages to Open Source Integration2mDemo: Getting Started with CAS and the R API18mDemo: Getting Started with CAS and the Python API18m

5 practice exercises

Question 2.0110mQuestion 2.0210mQuestion 2.0310mQuestion 2.0410mSAS® Viya® and Open Source Integration Quiz30m

Week2

Week 2

4 hours to complete

Machine Learning

4 hours to complete

15 videos (Total 104 min)

15 videos

Introduction to Predictive Modeling1mData Partitioning: Preventing Overfitting2mLogistic Regression Models3mSupport Vector Machines2mDecision Trees2mEnsemble of Trees2mNeural Network Models3mAutotuning Hyperparameters1mModel Performance Assessment2mModel Performance Charts: ROC and Lift2mDemo: Using the R API to Create and Assess Models26mDemo: Using the Python API to Create and Assess Models25mDemo: Creating a Gradient Boosting Model in SAS Studio7mDemo: Using R Functions and Looping for Efficient Coding10mDemo: Using Python Functions and Looping for Efficient Coding10m

4 practice exercises

Question 3.0110mQuestion 3.0210mQuestion 3.0310mMachine Learning Quiz30m

Week3

Week 3

2 hours to complete

Text Analytics

2 hours to complete

9 videos (Total 48 min)

3 hours to complete

Deep Learning

3 hours to complete

13 videos (Total 67 min)

13 videos

Traditional Neural Networks1mHidden Unit Activation Functions2mWeight Initialization1mRegularization Methods3mNonlinear Optimization Algorithms (or Gradient-Based Learning)3mProcessors for Analytics1mDeep Neural Networks (DNN) versus Recurrent Neural Networks (RNN)2mRecurrent Neural Network Architecture1mImproving RNN Models1mGated Recurrent Unit (GRU)2mLong Short-Term Memory (LSTM)2mDemo: Deep Learning Sentiment Prediction Using the R API21mDemo: Deep Learning Sentiment Prediction Using the Python API21m

3 practice exercises

Question 5.0110mQuestion 5.0210mDeep Learning Quiz30m

Week4

Week 4

3 hours to complete

Time Series

3 hours to complete

11 videos (Total 63 min)

11 videos

Time Series Forecasting2mModel Performance and Assessment2mWeighted Averages1mSimple Exponential Smoothing2mARIMAX Models and Stationarity1mAutoregressive and Moving Average Terms2mForecasting with Recurrent Neural Networks43sDemo: Automatic Forecasting Using the R API8mDemo: Automatic Forecasting Using the Python API8mDemo: Deep Learning Forecasting Using the R API16mDemo: Deep Learning Forecasting Using the Python API16m

4 practice exercises

Question 6.0110mQuestion 6.0210mQuestion 6.0310mTime Series Quiz30m

2 hours to complete

Image Classification

2 hours to complete

7 videos (Total 43 min)

2 hours to complete

Factorization Machines

2 hours to complete

4 videos (Total 29 min)

Reviews

4.6

3 reviews

5 stars
85.71%
4 stars
7.14%
1 star
7.14%

TOP REVIEWS FROM USING SAS VIYA REST APIS WITH PYTHON AND R

by RMOct 18, 2021

Grateful to the instructors! Thank you for enhancing my skills set.

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Using SAS Viya REST APIs with Python and R

Using SAS Viya REST APIs with Python and R

About this Course