SAS Enterprise Miner: Data Mining and Predictive Modeling

SAS Enterprise Miner: Data Mining and Predictive Modeling, available at $19.99, has an average rating of 4.75, with 61 lectures, based on 8 reviews, and has 4395 subscribers.

You will learn about Introduction to SAS Enterprise Miner and its capabilities for predictive modeling and data mining. Importing datasets in various formats such as text, CSV, xlsx, and xls. Understanding user operating concepts and software menus within SAS Enterprise Miner. Exploring statistical concepts like mean, standard deviation, and sample statistics. Performing variable selection using techniques like input variables, R-square values, and binary target variables. Combining different modeling techniques such as decision trees, neural networks, and regression models for enhanced predictive accuracy. Building and evaluating neural network models, including model weight history, ROC charts, and iteration plots. Implementing regression analysis with binary targets, interpreting regression model results, and creating effect plots. Engaging in practical exercises, case studies, and interactive discussions to reinforce learning. This course is ideal for individuals who are Data analysts and scientists seeking to deepen their understanding of advanced analytics tools. or Business intelligence professionals aiming to leverage predictive modeling for decision-making. or Students and academics interested in learning practical applications of statistical modeling. or Professionals in industries such as finance, healthcare, marketing, and retail looking to apply predictive analytics to their domain-specific datasets. or Anyone keen on mastering techniques like variable selection, neural networks, regression analysis, and decision trees using SAS Enterprise Miner. It is particularly useful for Data analysts and scientists seeking to deepen their understanding of advanced analytics tools. or Business intelligence professionals aiming to leverage predictive modeling for decision-making. or Students and academics interested in learning practical applications of statistical modeling. or Professionals in industries such as finance, healthcare, marketing, and retail looking to apply predictive analytics to their domain-specific datasets. or Anyone keen on mastering techniques like variable selection, neural networks, regression analysis, and decision trees using SAS Enterprise Miner.

Enroll now: SAS Enterprise Miner: Data Mining and Predictive Modeling

Summary

Title: SAS Enterprise Miner: Data Mining and Predictive Modeling

Price: $19.99

Average Rating: 4.75

Number of Lectures: 61

Number of Published Lectures: 61

Number of Curriculum Items: 61

Number of Published Curriculum Objects: 61

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

• Introduction to SAS Enterprise Miner and its capabilities for predictive modeling and data mining.
• Importing datasets in various formats such as text, CSV, xlsx, and xls.
• Understanding user operating concepts and software menus within SAS Enterprise Miner.
• Exploring statistical concepts like mean, standard deviation, and sample statistics.
• Performing variable selection using techniques like input variables, R-square values, and binary target variables.
• Combining different modeling techniques such as decision trees, neural networks, and regression models for enhanced predictive accuracy.
• Building and evaluating neural network models, including model weight history, ROC charts, and iteration plots.
• Implementing regression analysis with binary targets, interpreting regression model results, and creating effect plots.
• Engaging in practical exercises, case studies, and interactive discussions to reinforce learning.

Who Should Attend

• Data analysts and scientists seeking to deepen their understanding of advanced analytics tools.
• Business intelligence professionals aiming to leverage predictive modeling for decision-making.
• Students and academics interested in learning practical applications of statistical modeling.
• Professionals in industries such as finance, healthcare, marketing, and retail looking to apply predictive analytics to their domain-specific datasets.
• Anyone keen on mastering techniques like variable selection, neural networks, regression analysis, and decision trees using SAS Enterprise Miner.

Target Audiences

• Data analysts and scientists seeking to deepen their understanding of advanced analytics tools.
• Business intelligence professionals aiming to leverage predictive modeling for decision-making.
• Students and academics interested in learning practical applications of statistical modeling.
• Professionals in industries such as finance, healthcare, marketing, and retail looking to apply predictive analytics to their domain-specific datasets.
• Anyone keen on mastering techniques like variable selection, neural networks, regression analysis, and decision trees using SAS Enterprise Miner.