RiseUpp Logo
RiseUpp Logo
Cluster Analysis, Association Mining, and Model Evaluation
Educator Logo

Powered by

Provider Logo

Completion

CERTIFICATE

Cluster Analysis, Association Mining, and Model Evaluation

This course is part of Data Science Fundamentals.

Course Cost

Free course

Intermediate

Skill Level

4 Hours

Self-paced Video lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Science Fundamentals Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.6

4,372 Enrolled

English

4.6

4,372 Enrolled

English

What you'll learn

  • Apply cluster analysis for market segmentation

  • Implement collaborative filtering and association rules

  • Evaluate classification model performance

  • Develop regression-based prediction models

  • Understand supervised vs unsupervised learning applications

Skills you'll gain

Cluster Analysis
Market Basket Analysis
Model Evaluation
Data Mining
Collaborative Filtering
Association Rules
Segmentation
Classification Models
Regression Analysis
Prediction Models

This course includes:

0.1 Hours PreRecorded video

2 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

CREATED BY

Educator Logo

PROVIDED BY

Provider Logo
Certificate
Certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

CREATED BY

Educator Logo

PROVIDED BY

Provider Logo

Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

icon-0icon-1icon-2icon-3icon-4

There are 4 modules in this course

This comprehensive course explores key data mining techniques and evaluation methods. Students learn cluster analysis for market segmentation, collaborative filtering for recommendation systems, and association rules mining for market basket analysis. The curriculum covers both classification and regression-type prediction models, with emphasis on performance evaluation and practical applications across different industries.

Cluster Analysis and Segmentation

Module 1 · 1 Hours to complete

Collaborative Filtering, Association Rules Mining (Market Basked Analysis)

Module 2 · 42 Minutes to complete

Classification-Type Prediction Models

Module 3 · 59 Minutes to complete

Regression-Type Prediction Models

Module 4 · 1 Hours to complete

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Data Science Fundamentals

Reviews

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Cluster Analysis, Association Mining, and Model Evaluation

Intermediate

Skill Level

4 Hours

Self-paced Video lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.