ACSC 3740

Predictive Analytics

Lec 01 selected

This course teaches students to analyze data in a real-world context, going through all stages of the data analysis: problem formulation; initial data exploration; model selection and validation; and communication of results. It is intended that this course should prepare students for the Society of Actuaries Predictive Analytics examination.

Sections

Lecture

From the syllabus

From the Winter 2025 syllabus by Toby Kenney. Open the PDF

Grading

40%ProjectDue April 14
40%Final examOnline during the final exam period; date TBA
20%Assignments (5)Best 4 of 5; due dates Jan 24, Feb 7, Feb 28, Mar 21, Apr 4

Textbooks

  • Regression Modeling with Actuarial and Financial Applications, Edward W. Frees
  • An Introduction to Statistical Learning, with Applications in R, James, Witten, Hastie, Tibshirani
  • Data Visualization: A Practical Introduction, Healy

Course rules

Late assignments
Late assignments receive zero because solutions are posted online immediately after the due date.
Missed final exam
Notify the instructor before the exam when possible and submit the Student Declaration of Absence; reasonable efforts will be made to provide a make-up exam.
Submission format
Online assignments must be submitted in PDF or JPEG format.

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