Über diesen Kurs
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Englisch

Untertitel: Englisch

100 % online

Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.

Flexible Fristen

Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.

Englisch

Untertitel: Englisch

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche
1
1 Stunde zum Abschließen

Course Overview

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

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1 Video (Gesamt 1 min), 4 Lektüren, 1 Quiz
1 Video
4 Lektüren
Learner Prerequisites1m
Using SAS® Viya® for Learners with This Course (Required)10m
Course Information (Required)10m
Using Forums and Getting Help5m
2 Stunden zum Abschließen

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 (Gesamt 55 min), 6 Quiz
10 Videos
Cloud Analytic Services2m
Jupyter Notebooks and Open Source Development Interfaces2m
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 praktische Übungen
Question 2.0110m
Question 2.0210m
Question 2.0310m
Question 2.0410m
SAS® Viya® and Open Source Integration Quiz30m
Woche
2
4 Stunden zum Abschließen

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 (Gesamt 107 min), 8 Quiz
15 Videos
Data Partitioning: Preventing Overfitting2m
Logistic Regression Models3m
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 praktische Übungen
Question 3.0110m
Question 3.0210m
Question 3.0310m
Machine Learning Quiz30m
Woche
3
2 Stunden zum Abschließen

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 (Gesamt 48 min), 5 Quiz
9 Videos
Natural and Formal Languages1m
Processing Words1m
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 praktische Übungen
Question 4.0110m
Question 4.0210m
Text Analytics Quiz30m
3 Stunden zum Abschließen

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 (Gesamt 67 min), 5 Quiz
13 Videos
Hidden Unit Activation Functions2m
Weight Initialization1m
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 praktische Übungen
Question 5.0110m
Question 5.0210m
Deep Learning Quiz30m
Woche
4
3 Stunden zum Abschließen

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 (Gesamt 63 min), 6 Quiz
11 Videos
Model Performance and Assessment2m
Weighted Averages1m
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
4 praktische Übungen
Question 6.0110m
Question 6.0210m
Question 6.0310m
Time Series Quiz30m
2 Stunden zum Abschließen

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 (Gesamt 43 min), 4 Quiz
7 Videos
Convolutional Neural Networks for Image Classification1m
Convolution Layers3m
Pooling Layers1m
Fully Connected and Output Layers59
Demo: Classifying Color Images Using the R API16m
Demo: Classifying Color Images Using the Python API16m
2 praktische Übungen
Question 7.0110m
Image Classification Quiz30m
2 Stunden zum Abschließen

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 Videos (Gesamt 29 min), 4 Quiz
4 Videos
Factorization Machines for Recommendation3m
Demo: Modeling Sparse Data Using the R API11m
Demo: Modeling Sparse Data Using the Python API11m
2 praktische Übungen
Question 8.0110m
Factorization Machines Quiz30m

Dozenten

Avatar

Jordan Bakerman

Analytical Training Consultant
Education

Ari Zitin

Analytical Training Consultant
SAS Education

Über 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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