Acerca de este Curso
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Inglés (English)

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Programa - Qué aprenderás en este curso

Semana
1
1 hora para completar

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 minutos), 4 readings, 1 quiz
1 video
4 lecturas
Learner Prerequisites1m
Using SAS® Viya® for Learners with This Course (Required)10m
Course Information (Required)10m
Using Forums and Getting Help5m
2 horas para completar

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 minutos), 6 quizzes
10 videos
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
5 ejercicios de práctica
Question 2.0110m
Question 2.0210m
Question 2.0310m
Question 2.0410m
SAS® Viya® and Open Source Integration Quiz30m
Semana
2
4 horas para completar

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.

...
15 videos (Total 107 minutos), 8 quizzes
15 videos
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
4 ejercicios de práctica
Question 3.0110m
Question 3.0210m
Question 3.0310m
Machine Learning Quiz30m
Semana
3
2 horas para completar

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 minutos), 5 quizzes
9 videos
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
3 ejercicios de práctica
Question 4.0110m
Question 4.0210m
Text Analytics Quiz30m
3 horas para completar

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 minutos), 5 quizzes
13 videos
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
3 ejercicios de práctica
Question 5.0110m
Question 5.0210m
Deep Learning Quiz30m
Semana
4
3 horas para completar

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 videos (Total 63 minutos), 6 quizzes
11 videos
Simple Exponential Smoothing2m
ARIMAX Models and Stationarity1m
Autoregressive and Moving Average Terms2m
Forecasting with Recurrent Neural Networks43s
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
4 ejercicios de práctica
Question 6.0110m
Question 6.0210m
Question 6.0310m
Time Series Quiz30m
2 horas para completar

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.

...
7 videos (Total 43 minutos), 4 quizzes
7 videos
Pooling Layers1m
Fully Connected and Output Layers59s
Demo: Classifying Color Images Using the R API16m
Demo: Classifying Color Images Using the Python API16m
2 ejercicios de práctica
Question 7.0110m
Image Classification Quiz30m
2 horas para completar

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 minutos), 4 quizzes
4 videos
Demo: Modeling Sparse Data Using the Python API11m
2 ejercicios de práctica
Question 8.0110m
Factorization Machines Quiz30m

Instructores

Avatar

Jordan Bakerman

Analytical Training Consultant
Education

Ari Zitin

Analytical Training Consultant
SAS Education

Acerca de 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....

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.

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