Predictive Modeling Fundamentals I

Take our free course

Predictive Modelling

Predictive Modeling Fundamentals I

with Mikhail Lakirovich, Greg Filla and Armand Ruiz

Audience:
Data scientists, data analysts and anyone interested in Predictive Analytics

Time to complete:
8 hours

Available in:
English

Predictive Analytics brings together advanced analytics capabilities spanning ad-hoc statistical analysis, predictive modeling, data mining, text analytics, entity analytics, optimization, real-time scoring, machine learning and more. IBM SPSS Modeler puts these capabilities into the hands of business users, data scientists, and developers.

In this course in the Big Data University you will learn the basics to get started with Predictive Modeling.

Course Syllabus

After completing this course, you should be able to:

  • Describe what Predictive Modeling is all about and know why you would want to use it
  • Understand the CRISP-DM methodology and the IBM SPSS Modeler Workbench
  • Understand Common Modeling Techniques
  • Use IBM SPSS Modeler to solve a Kaggle competition
  • Explore, Prepare, Model and Evaluate your data using IBM SPSS Modeler

General Information

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be taken as many times as you wish.
  • Students passing the course (by passing the final exam) will have immediate access to printing their online certificate of achievement.
  • Your name in the certificate will appear exactly as entered in your profile in BigDataUniversity.com.
  • If you did not pass the course, you can take it again at any time.

Pre-requisites

  • None

Recommended skills prior to taking this course

  • Basic knowledge of business statistics (recommended but not required)

Grading Scheme

The minimum passing mark for the course is 60%, where the final test is worth 100% of the course mark. You have 3 attempts to take the test