Artificial Neural Networks for Business Managers in RStudio

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Paid

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Intermediate

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Free

Last updated on June 20, 2025 11:07 pm

Learn where and how to build ANN models in R to create predictive models that can guide crucial business decisions with this free online course.

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This free online course provides a solid foundation for a career in artificial neural networks (ANN) and deep learning. We explain how ANN can be applied to create predictive models capable of informing financial decisions. We take you step by step through the process of building ANN models in ?R? with RStudio until you can create your own machine learning algorithms. This course can help you to predict financial shifts in time to plan for them.

What You Will Learn In This Free Course

  • Describe the basic structure of a ne…
  • Identify the classification and regr…
  • Define ?Keras? and ?Tensorflow?…
  • Explain the steps to build a neural …
  • Describe the basic structure of a neural network
  • Identify the classification and regression hyperparameters
  • Define ?Keras? and ?Tensorflow?
  • Explain the steps to build a neural network model in R using the Keras package
  • Summarize the process of building a neural network for a regression problem
  • Evaluate the advantages of using the functional API in neural networks
  • Discuss the importance of outlier treatment, missing value imputation and seasonality
  • Outline the steps of variable transformation in R
  • Outline the ?least square? approach to linear regression
  • Analyze the accuracy of the linear regression model
  • ANN Overview

    This module introduces you to Artificial Neural Networks (ANN), starting with the concept of perception, through activation functions, to complex networks. You will also gain a basic understanding of how neural networks are formed, their architecture, and hyperparameters.

    Setting up RStudio and R Crash Course

    In this module, you will earn the basics of R and RStudio, starting from the installation processes. You will get an overview of the RStudio environment, the R commands you can use to input data, and the packages and data available in R. You will also learn to create graphs, change colours, and save the graphs.

    Neural Network Models

    This module demonstrates how to build neural network models using Keras and Neural nets. You will also learn about building regression models and using the Functional API. Finally, you will see how you can save your model in a separate file and restore or share it, when required.

    Data Preprocessing

    In this module, you will learn how to prepare the data for analysis. It starts with the basic theory of decision tree, where you will learn concepts such as Data Dictionary and Univariate Analysis. It then covers data pre-processing topics like outlier treatment, missing value imputation, variable transformation, and Test-Train split.

    Linear Regression

    This module starts with simple linear regression and then covers multiple linear regression in R. You will begin by understanding the basic concepts and then learn to quantify a model’s accuracy and the meaning of F statistic. You will also learn to interpret the variables in the dataset, and the result of the regression problem.

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      Artificial Neural Networks for Business Managers in RStudio
      Artificial Neural Networks for Business Managers in RStudio
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