About this Course

19,646 recent views
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 24 hours to complete
English
Subtitles: English

Skills you will gain

Predictive AnalyticsDecision-Making SoftwareGeodemographic SegmentationValidated Learning
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 24 hours to complete
English
Subtitles: English

Offered by

Placeholder

University of Illinois at Urbana-Champaign

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Accountancy (iMSA) from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your courses count towards your degree learning.

Syllabus - What you will learn from this course

Week
1

Week 1

9 hours to complete

Module 0: Get Ready & Module 1: Drowning in Data, Starving for Knowledge

9 hours to complete
13 videos (Total 104 min), 11 readings, 4 quizzes
13 videos
Meet Professor Sridhar Seshadri1m
Rattle Installation Guidelines for Windows11m
R and Rattle Installation Instructions for Mac OS14m
Overview of Rattle7m
Lecture 1-1: Introduction to Clustering11m
Lecture 1-2: Applications of Clustering7m
Lecture 1-3: How to Cluster10m
Lecture 1-4: Introduction to K Means8m
Lecture 1-5: Hierarchical (Agglomerative) Clustering8m
Lecture 1-6: Measuring Similarity Between Clusters10m
Lecture 1-7: Real World Clustering Example6m
Lecture 1-8: Clustering Practice and Summary3m
11 readings
Syllabus30m
About the Discussion Forums10m
Glossary10m
Brand Descriptions10m
Update Your Profile10m
Module 0 Agenda5m
Rattle Tutorials (Interface, Windows, Mac)30m
Frequent Asked Questions10m
Module 1 Overview20m
Module 1 Readings, Data Sets, and Slides1h 30m
Module 1 Peer Review Assignment Answer Key10m
3 practice exercises
Orientation Quiz30m
Module 1 Practice Problems10m
Module 1 Graded Quiz30m
Week
2

Week 2

5 hours to complete

Module 2: Decision Trees

5 hours to complete
7 videos (Total 65 min), 3 readings, 3 quizzes
7 videos
Lecture 2-2: Model Complexity7m
Lecture 2-3: Rule Based Classifiers9m
Lecture 2-4: Entropy and Decision Trees14m
Lecture 2-5: Classification Tree Example7m
Lecture 2-6: Regression Tree Example8m
Lecture 2-7: Introduction to Forests and Spam Filter Exercise9m
3 readings
Module 2 Overview20m
Module 2 Readings, Data Sets, and Slides30m
Module 2 Peer Review Assignment Answer Key10m
2 practice exercises
Module 2 Practice Problems30m
Module 2 Graded Quiz30m
Week
3

Week 3

5 hours to complete

Module 3: Rules, Rules, and More Rules

5 hours to complete
8 videos (Total 65 min), 3 readings, 3 quizzes
8 videos
Lecture 3-2: K-Nearest Neighbor9m
Lecture 3-3: K-Nearest Neighbor Classifier3m
Lecture 3-4: Selecting the Best K in Rstudio12m
Lecture 3-5: Bayes' Rule7m
Lecture 3-6: The Naïve Bayes Trick13m
Lecture 3-7: Employee Attrition Example5m
Lecture 3-8: Employee Attrition Example in Rstudio, Exercise, and Summary9m
3 readings
Module 3 Overview20m
Module 3 Readings, Data Sets, and Slides30m
Module 3 Peer Review Assignment Answer Key10m
2 practice exercises
Module 3 Practice Problems10m
Module 3 Graded Quiz30m
Week
4

Week 4

5 hours to complete

Module 4: Model Performance and Recommendation Systems

5 hours to complete
8 videos (Total 68 min), 3 readings, 3 quizzes
8 videos
Lecture 4-2: Classification Tree Example11m
Lecture 4-3: True and False Negatives8m
Lecture 4-4: Clock Example Exercise2m
Lecture 4-5: Making Recommendations13m
Lecture 4-6: Association Rule Mining6m
Lecture 4-7: Collaborative Filtering7m
Lecture 4-8: Recommendation Example in Rstudio and Summary12m
3 readings
Module 4 Overview20m
Module 4 Readings, Data Sets, and Slides1h
Module 4 Peer Review Assignment Answer Key10m
2 practice exercises
Module 4 Practice Problems10m
Module 4 Graded Quiz30m

Reviews

TOP REVIEWS FROM PREDICTIVE ANALYTICS AND DATA MINING

View all reviews

Frequently Asked Questions

More questions? Visit the Learner Help Center.