About this Course
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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

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일정에 따라 마감일을 재설정합니다.

영어

자막: 영어

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 1시간 필요

Course Overview

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

...
1 video (Total 1 min), 4 readings, 1 quiz
1개의 동영상
4개의 읽기 자료
Learner Prerequisites1m
Using SAS® Viya® for Learners with This Course (Required)10m
Course Information (Required)10m
Using Forums and Getting Help5m
완료하는 데 2시간 필요

SAS® Viya® and Open Source Integration

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.

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10 videos (Total 55 min), 6 quizzes
10개의 동영상
SAS Scripting Wrapper for Analytics Transfer2m
CAS Actions in SAS Viya2m
Connecting to CAS and Reading in Data1m
DataFrames and CAS Tables on the Clients and Server2m
Advantages to Open Source Integration2m
Demo: Getting Started with CAS and the R API18m
Demo: Getting Started with CAS and the Python API18m
5개 연습문제
Question 2.0110m
Question 2.0210m
Question 2.0310m
Question 2.0410m
SAS® Viya® and Open Source Integration Quiz30m
2
완료하는 데 4시간 필요

Machine Learning

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.

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15 videos (Total 107 min), 8 quizzes
15개의 동영상
Support Vector Machines2m
Decision Trees2m
Ensemble of Trees2m
Neural Network Models3m
Autotuning Hyperparameters1m
Model Performance Assessment2m
Model Performance Charts: ROC and Lift2m
Demo: Using the R API to Create and Assess Models26m
Demo: Using the Python API to Create and Assess Models25m
Demo: Creating a Gradient Boosting Model in SAS Studio7m
Demo: Using R Functions and Looping for Efficient Coding11m
Demo: Using Python Functions and Looping for Efficient Coding11m
4개 연습문제
Question 3.0110m
Question 3.0210m
Question 3.0310m
Machine Learning Quiz30m
3
완료하는 데 2시간 필요

Text Analytics

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.

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9 videos (Total 48 min), 5 quizzes
9개의 동영상
Processing Context2m
Processing Concepts1m
Extracting Information from the Term-Document Matrix3m
Word Embedding3m
Demo: Using the R API to Explore Text Documents15m
Demo: Using the Python API to Explore Text Documents15m
3개 연습문제
Question 4.0110m
Question 4.0210m
Text Analytics Quiz30m
완료하는 데 3시간 필요

Deep Learning

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.

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13 videos (Total 67 min), 5 quizzes
13개의 동영상
Regularization Methods3m
Nonlinear Optimization Algorithms (or Gradient-Based Learning)3m
Processors for Analytics1m
Deep Neural Networks (DNN) versus Recurrent Neural Networks (RNN)2m
Recurrent Neural Network Architecture1m
Improving RNN Models1m
Gated Recurrent Unit (GRU)2m
Long Short-Term Memory (LSTM)2m
Demo: Deep Learning Sentiment Prediction Using the R API21m
Demo: Deep Learning Sentiment Prediction Using the Python API21m
3개 연습문제
Question 5.0110m
Question 5.0210m
Deep Learning Quiz30m
4
완료하는 데 3시간 필요

Time Series

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.

...
11 videos (Total 63 min), 6 quizzes
11개의 동영상
Simple Exponential Smoothing2m
ARIMAX Models and Stationarity1m
Autoregressive and Moving Average Terms2m
Forecasting with Recurrent Neural Networks43
Demo: Automatic Forecasting Using the R API8m
Demo: Automatic Forecasting Using the Python API8m
Demo: Deep Learning Forecasting Using the R API16m
Demo: Deep Learning Forecasting Using the Python API16m
4개 연습문제
Question 6.0110m
Question 6.0210m
Question 6.0310m
Time Series Quiz30m
완료하는 데 2시간 필요

Image Classification

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.

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7 videos (Total 43 min), 4 quizzes
7개의 동영상
Pooling Layers1m
Fully Connected and Output Layers59
Demo: Classifying Color Images Using the R API16m
Demo: Classifying Color Images Using the Python API16m
2개 연습문제
Question 7.0110m
Image Classification Quiz30m
완료하는 데 2시간 필요

Factorization Machines

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.

...
4 videos (Total 29 min), 4 quizzes
4개의 동영상
Demo: Modeling Sparse Data Using the Python API11m
2개 연습문제
Question 8.0110m
Factorization Machines Quiz30m

강사

Avatar

Jordan Bakerman

Analytical Training Consultant
Education

Ari Zitin

Analytical Training Consultant
SAS Education

SAS 정보

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....

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 수료증을 구매하면 성적 평가 과제를 포함한 모든 강좌 자료에 접근할 수 있습니다. 강좌를 완료하면 전자 수료증이 성취도 페이지에 추가되며, 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 콘텐츠만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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