Advanced Topics in Predictive Analytics Video Course and Study Guide 1st Edition Author: Lo and Li

ISBN(s): 979-8-89016-254-0 | 979-8-89016-255-7

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Printed manual ships week of January 13th

Advance your learning to conquer this assessment.

These two tools can help you learn and be prepared to take the 96 hour assessment.

  • Study manual - read, learn and gain a strong conceptual understanding of the material
  • Instructional Videos - gain deep understanding and visuals to bring extra to your learning

Study Guide For SOA Advanced Topics in Predictive Analytics (ATPA) Assessment

Building on the success of the ACTEX PA study guide, this brand new ATPA study guide provides a self-contained and comprehensive treatment of the materials of the ATPA Assessment, streamlined and augmented in a coherent and exam-oriented format. With a nice blend of theory and practice, it presents the theory of different types of advanced predictive analytic models in the syllabus and illustrates them by a set of R-based case studies.

Using the sample code in the manual as a foundation for your ATPA Assessment preparation is invaluable. You'll gain hands-on experience manipulating complex datasets, understanding how models operate, and implementing them step by step in R. These skills are essential for mastering the assessment and achieving success. Drawing upon his battle experience of taking (and passing!) the real assessment in 2023, the author will also share with you his exam insights and what it takes to frame your written responses to the liking of ATPA exam graders.

ATPA Assessment Video Course

The Advanced Topics in Predictive Analytics video course is designed to help you more easily climb the steep ATPA learning curve. This instructional video course will allow you to write your ATPA exam more confidently, and increase your chances of passing the exam.

This Module-focused Video Course includes:

  • 15+ Videos (6 hours) meticulously organized into three modules, helping you achieve the learning objective of this course with ease:
    • Additive Models
    • Linear Mixed Models
    • Neural Networks
  • 3 end-of-module assessments to evaluate your understanding of the material
  • Lecture slides so you can follow along with the instructor and take notes
  • Access to the instructor during the duration of the course
  • Access to a discussion forum to ask questions and see what other students are saying
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