More Data Mining with R
How to perform market basket analysis, analyze social networks, mine Twitter data, text, and time series data.
Affiliate disclosure: if you enroll through links on this page, the course provider may pay us a commission. This comes at no extra cost to you and does not influence how we describe courses.
What You'll Learn in This Course
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Learning Outcome 1
Understand the conceptual foundations of association analysis and perform market basket analyses.
Learning Outcome 2
Be able to create visualizations of social (and other) networks using the iGraph package.
Learning Outcome 3
Understand how to examine and mine social network data to understand all of the implicit relationships.
Learning Outcome 4
Mine text data to create word association visualizations, term documents with word frequency counts and associations, and create word clouds.
Learning Outcome 5
Learn how to process text and string data, including the use of 'regular expressions'.
Skills You'll Develop
This comprehensive More Data Mining with R curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Course Requirements & Target Audience
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
Prerequisites & Requirements
What you need before starting this More Data Mining with R course:
- Students will need to install the no-cost R console software and the no-cost RStudio IDE suite (instructions are provided).
Who This Course Is For
This course is perfect for:
- Motivated learners at any level
- Self-paced students
- Anyone interested in the subject
This course might not be suitable if:
- • You're looking for a quick tutorial rather than comprehensive learning
- • You prefer learning without structured curriculum
- • You need highly specialized or niche content
Course Information & Details
Everything you need to know about this online course, from duration to certification
Course Instructor
Geoffrey Hubona, Ph.D.
Expert instructor with industry experience
Course Language
English
All materials in English
Start Your Learning Journey Today
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
Course Enrollment
Comprehensive Program
Professional training from $174.99
Pricing may vary. Check the course provider for current promotions and exact pricing.
What's Included
- 10.5 hours on-demand video
- 10 downloadable resources
- Access on mobile and TV
- Certificate of Completion
- Full lifetime access
Affiliate disclosure: if you enroll through links on this page, the course provider may pay us a commission. This comes at no extra cost to you and does not influence how we describe courses.
- ✓Instant access after enrollment
- ✓Learn at your own pace
- ✓Direct enrollment with Udemy
Where this course fits
Certifications in this area
- Microsoft Certified: Azure Data Fundamentals · Foundational
- Microsoft Certified: Azure AI Fundamentals · Foundational
- AWS Certified AI Practitioner · Foundational
- Microsoft Certified: Fabric Data Engineer Associate · Associate
- Microsoft Certified: Power BI Data Analyst Associate · Associate
- Databricks Certified Data Engineer Associate · Associate
Concepts behind this area
Machine Learning
Machine learning is the branch of computing in which a program works out its rule from examples instead of being handed that rule by a programmer, and is judged on how well the rule holds on cases it was never shown.
Neural Networks
A neural network is a stack of layers of very simple arithmetic units whose connection strengths are adjusted by training until the whole arrangement turns the inputs you have into the outputs you want.
Deep Learning
Deep learning is machine learning built on neural networks of many stacked layers, which work out for themselves which properties of the raw data matter instead of being handed a list by a person.
Data Analysis
Data analysis is the practice of interrogating data to answer a specific question, and of establishing how much weight the answer can bear.
Data Wrangling
Data wrangling is the work of repairing and reshaping real records, and of deciding what their gaps and inconsistencies mean, until a table can be trusted with the question being asked of it.
Data Visualization
Data visualisation is the practice of encoding numbers as position, length and colour so that a comparison a reader would otherwise have to calculate becomes something they can simply see.
The field, explained: Artificial Intelligence & Machine Learning · Data & Analytics
Wider context: the fields we cover, the glossary and certification exams, all written by us rather than pulled from a provider feed.
