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Updated in [August 13th, 2023]

Skills and Knowledge Acquired:
By taking this course, students will acquire skills and knowledge in data mining, the CRISP-DM methodology, navigating within Modeler, reading data into Modeler, describing, exploring, and assessing data quality, integrating and constructing data, building predictive models, taking data mining results to achieve business objectives, and deploying findings.


Contribution to Professional Growth:
This course contributes to professional growth by providing students with the knowledge and skills necessary to use IBM SPSS Modeler to analyze data and build predictive models. Students will learn about the CRISP-DM methodology, how to read data into Modeler, how to describe, explore, and assess data quality, how to integrate and construct data, how to build a predictive model, how to take data mining results to achieve business objectives, and how to deploy the findings. With this knowledge, students will be able to use IBM SPSS Modeler to analyze data and build predictive models in a professional setting.


Suitability for Further Education:
IBM SPSS Modeler: Getting Started is a suitable course for preparing further education. It provides an introduction to data mining and the functionality available within IBM SPSS Modeler. The course is broken up into phases, which cover topics such as data mining, data understanding, data preparation, modeling, evaluation, and deployment. This course provides a comprehensive overview of the data mining process and provides the necessary skills to build predictive models. As such, it is suitable for preparing further education in the field of data mining.

Course Syllabus

Introduction to Data Mining

Data Understanding

Data Preparation

Modeling

Evaluation

Deployment