SAS Visual Forecasting

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Large-Scale Forecasting Using SAS Viya: A Programming Approach
This course teaches students to develop and maintain a large-scale forecasting project using SAS Visual Forecasting tools. For the course project, students build and then refine a large-scale forecasting system. Emphasis is initially on selecting appropriate methods for data creation and variable transformations, model generation, and model selection. Students are then asked to improve overall baseline forecasting performance by modifying default processes in the system.

3 zaawansowany e-Learning
Models for Time Series and Sequential Data
This course teaches students to build, refine, extrapolate, and, in some cases, interpret models designed for a single, sequential series. There are three modeling approaches presented. The traditional, Box-Jenkins approach for modeling time series is covered in the first part of the course. This presentation moves students from models for stationary data (or ARMA) to models for trend and seasonality (ARIMA) and concludes with information about specifying transfer function components in an ARIMAX, or time series regression, model. A Bayesian approach to modeling time series is considered next. The basic Bayesian framework is extended to accommodate autoregressive variation in the data as well as dynamic input variable effects. Machine learning algorithms for time series is the third approach. Gradient boosting and recurrent neural network algorithms are particularly well suited for accommodating nonlinear relationships in the data. Examples are provided to build intuition on the effective use of these algorithms. The course concludes by considering how forecasting precision can be improved by combining the strengths of the different approaches. The final lesson includes demonstrations of creating combined (or ensemble) and hybrid model forecasts.

3 zaawansowany e-Learning
Prognozowanie z użyciem Model Studio w SAS Viya
Kurs ten umożliwia praktyczne zapoznanie się z funkcjonalnością prognozowania w Model Studio, będącym częścią składową SAS Viya. Kurs rozpoczyna się od pokazania jak załadować dane do pamięci i wizualizacji danych szeregów czasowych, które mają być modelowane. Zmienne atrybutów są wprowadzane i implementowane w wizualizacji. Następnie kurs obejmuje podstawowe zagadnienia związane z wykorzystaniem potoków do generowania prognoz i wyborem potoków mistrzowskich w projekcie. Uczy on również, jak włączyć praktyki prognozowania na dużą skalę do projektu prognozowania. Obejmują one tworzenie hierarchii danych, uzgadnianie prognoz, nadpisywanie i najlepsze praktyki związane z wyborem modelu prognozy.

2 średnio zaawansowany Classroom Live Web Classroom e-Learning
Time Series Feature Mining and Creation
In this course, you learn about data exploration, feature creation, and feature selection for time sequences. The topics discussed include binning, smoothing, transformations, and data set operations for time series, spectral analysis, singular spectrum analysis, distance measures, and motif analysis.

3 zaawansowany e-Learning