Using SAS Viya REST APIs with Python and R

位教师：Jordan Bakerman

3,856 人已注册

包含在 Coursera Plus 中

了解更多

8个模块

深入了解一个主题并学习基础知识。

4.7

（15 条评论）

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

8个模块

深入了解一个主题并学习基础知识。

4.7

（15 条评论）

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将获得的技能

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

23 项作业

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

该课程共有8个模块

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.

In this module, you meet the instructor and learn about course logistics, such as how to access the software for this course.

涵盖的内容

1个视频4篇阅读材料1个应用程序项目

In this module you learn about the analytical processing engine behind SAS Viya, the Cloud Analytic Services server. You also learn how to submit data processing commands to SAS Viya from the open source languages R and Python.

涵盖的内容

10个视频5个作业1个应用程序项目

10个视频总计54分钟

SAS Approach to Open Source Integration2分钟
Cloud Analytic Services2分钟
Jupyter Notebooks and Open Source Development Interfaces2分钟
SAS Scripting Wrapper for Analytics Transfer2分钟
CAS Actions in SAS Viya2分钟
Connecting to CAS and Reading in Data1分钟
DataFrames and CAS Tables on the Clients and Server2分钟
Advantages to Open Source Integration2分钟
Demo: Getting Started with CAS and the R API18分钟
Demo: Getting Started with CAS and the Python API18分钟

5个作业总计70分钟

Question - CAS Server10分钟
Question - Jupyter Notebooks10分钟
Questions - SWAT and CAS Processing10分钟
Questions - Fundamentals10分钟
SAS® Viya® and Open Source Integration Quiz30分钟

1个应用程序项目总计20分钟

Practice - Exploring the Bank Promotion Data Set Using CAS20分钟

In this module you learn how to use R and Python to create, optimize, and assess SAS Viya predictive models. You also learn how to use R and Python to efficiently manage the creation and assessment of these models.

涵盖的内容

15个视频4个作业3个应用程序项目

15个视频总计104分钟

Introduction to Predictive Modeling1分钟
Data Partitioning: Preventing Overfitting2分钟
Logistic Regression Models3分钟
Support Vector Machines2分钟
Decision Trees2分钟
Ensemble of Trees2分钟
Neural Network Models3分钟
Autotuning Hyperparameters1分钟
Model Performance Assessment2分钟
Model Performance Charts: ROC and Lift2分钟
Demo: Using the R API to Create, Score, and Assess Models26分钟
Demo: Using the Python API to Create, Score, and Assess Models25分钟
Demo: Creating a Gradient Boosting Model in SAS Studio7分钟
Demo: Using R Functions and Loops for Efficient Coding10分钟
Demo: Using Python Functions and Loops for Efficient Coding10分钟

4个作业总计60分钟

Questions - Predictive Modeling10分钟
Questions - Predictive Models10分钟
Questions - Model Assessment10分钟
Machine Learning Quiz30分钟

3个应用程序项目总计45分钟

Access SAS Viya for Learners for Demos and Practices5分钟
Practice - Creating, Scoring, and Assessing Tree-Based Models20分钟
Practice - Efficient Coding with Functions and Loops20分钟

In this module you learn how natural language processing is used to analyze collections of text documents. You also learn how to turn blocks of unstructured text into numeric inputs suitable for predictive modeling.

涵盖的内容

9个视频3个作业2个应用程序项目

9个视频总计47分钟

Text Analytics3分钟
Natural and Formal Languages1分钟
Processing Words1分钟
Processing Context2分钟
Processing Concepts1分钟
Extracting Information from the Term-Document Matrix3分钟
Word Embedding3分钟
Demo: Using the R API to Explore Text Documents15分钟
Demo: Using the Python API to Explore Text Documents15分钟

3个作业总计50分钟

Questions - Text Analytics Fundamentals10分钟
Questions - Natural Language Processing10分钟
Text Analytics Quiz30分钟

2个应用程序项目总计25分钟

Access SAS Viya for Learners for Demos and Practices5分钟
Practice - Exploring Movie Description Text Documents20分钟

In this module you learn how deep learning methods extend traditional neural network models with new options and architectures. You also learn how recurrent neural networks are used to model sequence data like time series and text strings, and how to create these models using R and Python APIs for SAS Viya.

涵盖的内容

13个视频3个作业2个应用程序项目

13个视频总计67分钟

Traditional Neural Networks1分钟
Hidden Unit Activation Functions2分钟
Weight Initialization1分钟
Regularization Methods3分钟
Nonlinear Optimization Algorithms (or Gradient-Based Learning)3分钟
Processors for Analytics1分钟
Deep Neural Networks (DNN) versus Recurrent Neural Networks (RNN)2分钟
Recurrent Neural Network Architecture1分钟
Improving RNN Models1分钟
Gated Recurrent Unit (GRU)2分钟
Long Short-Term Memory (LSTM)2分钟
Demo: Deep Learning Sentiment Prediction Using the R API21分钟
Demo: Deep Learning Sentiment Prediction Using the Python API21分钟

3个作业总计50分钟

Questions - Traditional Neural Networks vs Deep Learning 10分钟
Questions - Recurrent Neural Networks10分钟
Deep Learning Quiz30分钟

2个应用程序项目总计25分钟

Access SAS Viya for Learners for Demos and Practices5分钟
Practice - Using Deep Learning to Classify Profitable Movies20分钟

In this module you learn how to model time series using two popular methods, exponential smoothing and ARIMAX. You also learn how to use the R and Python APIs for SAS Viya to create forecasts using these classical methods and using recurrent neural networks for more complex problems.

涵盖的内容

11个视频4个作业2个应用程序项目

11个视频总计62分钟

Time Series Forecasting2分钟
Model Performance and Assessment2分钟
Weighted Averages1分钟
Simple Exponential Smoothing2分钟
ARIMAX Models and Stationarity1分钟
Autoregressive and Moving Average Terms2分钟
Forecasting with Recurrent Neural Networks0分钟
Demo: Automatic Forecasting Using the R API8分钟
Demo: Automatic Forecasting Using the Python API8分钟
Demo: Deep Learning Forecasting Using the R API16分钟
Demo: Deep Learning Forecasting Using the Python API16分钟

4个作业总计60分钟

Questions Time Series Modeling and Forecasting10分钟
Questions - Exponential Smoothing Parameters10分钟
Questions - ARIMAX Models and Stationary Time Series10分钟
Time Series Quiz30分钟

2个应用程序项目总计40分钟

Access SAS Viya for Learners for Demos and Practices20分钟
Practice - Building a Long Short-Term Memory Recurrent Neural Network20分钟

In this module you learn how convolutional neural networks are used to classify images and how to use the R and Python APIs for SAS Viya to create convolutional neural networks.

涵盖的内容

7个视频2个作业2个应用程序项目

7个视频总计43分钟

Image Classification and Object Detection2分钟
Convolutional Neural Networks for Image Classification1分钟
Convolution Layers3分钟
Pooling Layers1分钟
Fully Connected and Output Layers0分钟
Demo: Classifying Color Images Using the R API16分钟
Demo: Classifying Color Images Using the Python API16分钟

2个作业总计40分钟

Questions Deep Learning Image Classification10分钟
Image Classification Quiz30分钟

2个应用程序项目总计25分钟

Access SAS Viya for Learners for Demos and Practices5分钟
Practice - Classifying Clothing Images Using a Convolutional Neural Network20分钟

In this module you learn how factorization machines are used to create recommendation engines and how to build factorization machine models in SAS Viya using the R and Python APIs.

涵盖的内容

4个视频2个作业2个应用程序项目

4个视频总计28分钟

Recommender Systems2分钟
Factorization Machines for Recommendation3分钟
Demo: Modeling Sparse Data Using the R API11分钟
Demo: Modeling Sparse Data Using the Python API11分钟

2个作业总计40分钟

Questions - Modeling Interactions in Factorization Machines10分钟
Factorization Machines Quiz30分钟

2个应用程序项目总计25分钟

Access SAS Viya for Learners for Demos and Practices5分钟
Practice - Modeling Sparse Ratings Using Factorization and Machines20分钟

位教师

Jordan Bakerman

SAS

4 门课程59,887 名学生

Ari Zitin

SAS

2 门课程5,263 名学生

提供方

SAS

从 Data Analysis 浏览更多内容

状态：预览
SAS
Machine Learning Using SAS Viya
课程
状态：免费试用
SAS
Data Analysis and Reporting in SAS Visual Analytics
课程
状态：免费试用
SAS
Getting Started with SAS Visual Analytics
课程
Packt
REST APIs with Flask and Python in 2024
课程

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

自 2018开始学习的学生

''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情，我就可以学习。'

Jennifer J.

自 2020开始学习的学生

''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

Larry W.

自 2021开始学习的学生

''如果我的大学不提供我需要的主题课程，Coursera 便是最好的去处之一。'

Chaitanya A.

''学习不仅仅是在工作中做的更好：它远不止于此。Coursera 让我无限制地学习。'

学生评论

4.7

15 条评论

5 stars
86.66%
4 stars
6.66%
3 stars
0%
2 stars
0%
1 star
6.66%

显示 3/15 个

已于 Oct 18, 2021审阅

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

查看更多评论

通过 Coursera Plus 开启新生涯

无限制访问 10,000+ 世界一流的课程、实践项目和就业就绪证书课程 - 所有这些都包含在您的订阅中

了解更多

通过在线学位推动您的职业生涯

获取世界一流大学的学位 - 100% 在线

探索学位

加入超过 3400 家选择 Coursera for Business 的全球公司

提升员工的技能，使其在数字经济中脱颖而出

了解更多

常见问题

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.