IT Professional Curricula     Enterprise Database Systems Solution Area     Data Science     Data Mining and Decision Making

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Data mining and data science are rapidly transforming decision-making business practices. For these activities to be worthwhile, raw data needs to be transformed into insights relevant to your business's goals.
In this course, you'll walk through each stage of the data mining pipeline covering all requirements for reaching a conclusive and relevant business decision.
You'll examine data preparation, descriptive and predictive analytics, and predictive modeling. You'll also investigate the role of model validation and implementation in machine learning.
On completion, you'll have a solid grasp of how data-driven decision-making has helped other businesses succeed and how it can help yours, too, if you employ the right methods.

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Objectives

Data Mining and Decision Making: Modern Data Science Lifecycle discover the key concepts covered in this course compare the roles of data science and data analysis in a business context name the steps and processes essential to any data science project specify how to establish the business perspective of a data science project and how business goals relate to data analysis and predictive modeling list the processes essential to preparing data and specify the goal of each process describe how descriptive analysis can be used to drive business decision-making describe how predictive analytics can be used to drive business decision-making name multiple ways in which predictive modeling should be interpreted through a business context define the role of model validation when using machine learning for predictive modelling specify the requirements for model implementation when using machine learning for predictive modeling outline how data-driven decision-making is used in a business context using the example of a case study summarize the key concepts covered in this course