Informações sobre o curso
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100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
1 hora para concluir

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 vídeo ((Total 1 mín.)), 4 leituras, 1 teste
1 vídeos
4 leituras
Learner Prerequisites1min
Using SAS® Viya® for Learners with This Course (Required)10min
Course Information (Required)10min
Using Forums and Getting Help5min
2 horas para concluir

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 vídeos ((Total 55 mín.)), 6 testes
10 videos
Cloud Analytic Services2min
Jupyter Notebooks and Open Source Development Interfaces2min
SAS Scripting Wrapper for Analytics Transfer2min
CAS Actions in SAS Viya2min
Connecting to CAS and Reading in Data1min
DataFrames and CAS Tables on the Clients and Server2min
Advantages to Open Source Integration2min
Demo: Getting Started with CAS and the R API18min
Demo: Getting Started with CAS and the Python API18min
5 exercícios práticos
Question 2.0110min
Question 2.0210min
Question 2.0310min
Question 2.0410min
SAS® Viya® and Open Source Integration Quiz30min
Semana
2
4 horas para concluir

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 vídeos ((Total 107 mín.)), 8 testes
15 videos
Data Partitioning: Preventing Overfitting2min
Logistic Regression Models3min
Support Vector Machines2min
Decision Trees2min
Ensemble of Trees2min
Neural Network Models3min
Autotuning Hyperparameters1min
Model Performance Assessment2min
Model Performance Charts: ROC and Lift2min
Demo: Using the R API to Create and Assess Models26min
Demo: Using the Python API to Create and Assess Models25min
Demo: Creating a Gradient Boosting Model in SAS Studio7min
Demo: Using R Functions and Looping for Efficient Coding11min
Demo: Using Python Functions and Looping for Efficient Coding11min
4 exercícios práticos
Question 3.0110min
Question 3.0210min
Question 3.0310min
Machine Learning Quiz30min
Semana
3
2 horas para concluir

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 vídeos ((Total 48 mín.)), 5 testes
9 videos
Natural and Formal Languages1min
Processing Words1min
Processing Context2min
Processing Concepts1min
Extracting Information from the Term-Document Matrix3min
Word Embedding3min
Demo: Using the R API to Explore Text Documents15min
Demo: Using the Python API to Explore Text Documents15min
3 exercícios práticos
Question 4.0110min
Question 4.0210min
Text Analytics Quiz30min
3 horas para concluir

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 vídeos ((Total 67 mín.)), 5 testes
13 videos
Hidden Unit Activation Functions2min
Weight Initialization1min
Regularization Methods3min
Nonlinear Optimization Algorithms (or Gradient-Based Learning)3min
Processors for Analytics1min
Deep Neural Networks (DNN) versus Recurrent Neural Networks (RNN)2min
Recurrent Neural Network Architecture1min
Improving RNN Models1min
Gated Recurrent Unit (GRU)2min
Long Short-Term Memory (LSTM)2min
Demo: Deep Learning Sentiment Prediction Using the R API21min
Demo: Deep Learning Sentiment Prediction Using the Python API21min
3 exercícios práticos
Question 5.0110min
Question 5.0210min
Deep Learning Quiz30min
Semana
4
3 horas para concluir

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.

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11 vídeos ((Total 63 mín.)), 6 testes
11 videos
Model Performance and Assessment2min
Weighted Averages1min
Simple Exponential Smoothing2min
ARIMAX Models and Stationarity1min
Autoregressive and Moving Average Terms2min
Forecasting with Recurrent Neural Networks43s
Demo: Automatic Forecasting Using the R API8min
Demo: Automatic Forecasting Using the Python API8min
Demo: Deep Learning Forecasting Using the R API16min
Demo: Deep Learning Forecasting Using the Python API16min
4 exercícios práticos
Question 6.0110min
Question 6.0210min
Question 6.0310min
Time Series Quiz30min
2 horas para concluir

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 vídeos ((Total 43 mín.)), 4 testes
7 videos
Convolutional Neural Networks for Image Classification1min
Convolution Layers3min
Pooling Layers1min
Fully Connected and Output Layers59s
Demo: Classifying Color Images Using the R API16min
Demo: Classifying Color Images Using the Python API16min
2 exercícios práticos
Question 7.0110min
Image Classification Quiz30min
2 horas para concluir

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.

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4 vídeos ((Total 29 mín.)), 4 testes
4 videos
Factorization Machines for Recommendation3min
Demo: Modeling Sparse Data Using the R API11min
Demo: Modeling Sparse Data Using the Python API11min
2 exercícios práticos
Question 8.0110min
Factorization Machines Quiz30min

Instrutores

Avatar

Jordan Bakerman

Analytical Training Consultant
Education

Ari Zitin

Analytical Training Consultant
SAS Education

Sobre 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....

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você adquire o Certificado, ganha acesso a todo o material do curso, incluindo avaliações com nota atribuída. Após concluir o curso, seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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