Modern enterprises capture significant amounts of data about its customers, suppliers, and partners. The challenge, however, is to transform this vast data repository into actionable business intelligence. This course introduces predictive analytics tools that can provide valuable business insights. Analysis tools include decision trees, neural networks, market basket analysis, and discriminant analysis. Both data cleaning and analyses will be discussed and applied to sample data.
Predictive Analytics
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
6 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
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Recently updated!
September 2025
Assessments
27 assignments
Taught in English
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There are 9 modules in this course
Welcome to Predictive Analytics! Module 1 introduces the R programming environment and the basics of writing code in R.
What's included
10 videos6 readings4 assignments1 discussion prompt1 ungraded lab
In Module 2, you will learn the basics of Classification and understand the working of the kNN classifier.
What's included
9 videos4 readings4 assignments1 ungraded lab
To effectively learn Naive Bayes classification, this module will cover both the theoretical foundations and the practical implementation in R.
What's included
5 videos3 readings3 assignments1 ungraded lab
In order to understand the working of the Decision Tree as a classifier , we will need to grasp how this algorithm makes decisions and classifies new data points based on patterns it learned from training data.
What's included
5 videos3 readings3 assignments1 ungraded lab
This module focused on "Using Artificial Neural Networks (ANNs) as a classifier" aims to provide a comprehensive understanding of how these powerful, biologically inspired models can be applied to categorize data.
What's included
6 videos3 readings3 assignments1 ungraded lab
This module, "Classification using Support Vector Machines (SVMs)", will equip you with a deep understanding of this powerful machine learning algorithm and its application in classifying data.
What's included
4 videos3 readings3 assignments1 ungraded lab
This module on "Clustering" aims to introduce you to the powerful world of unsupervised learning, where the goal is to discover inherent groupings within unlabeled data.
What's included
4 videos3 readings3 assignments1 ungraded lab
Mining frequent item sets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
What's included
4 videos3 readings3 assignments1 ungraded lab
This module contains the summative course assessment that has been designed to evaluate your understanding of the course material and assess your ability to apply the knowledge you have acquired throughout the course.
What's included
1 assignment
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