Programming Statistical Applications in R
An introductory course that teaches the foundations of scientific and statistical programming using R software.
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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 how to create and manipulate R data structures used in scientific programming applications.
Learning Outcome 2
Understand and use important statistical R programming concepts such as looping and control structures, interactive data input and formatting output, writing functions as programs, writing output to a file and plotting output.
Learning Outcome 3
Understand and be able to use the R apply family of functions efficiently.
Learning Outcome 4
Know how to debug programs and how to make programs run more efficiently.
Learning Outcome 5
Understand and be able to implement various resampling methods effectively, including bootstrapping, jackknifing and N-fold cross validation.
Skills You'll Develop
This comprehensive Programming Statistical Applications in 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 Programming Statistical Applications in R course:
- Students will need to install the popular no-cost R Console and RStudio software (instructions 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
Professional Course
Investment around $74.99
Pricing may vary. Check the course provider for current promotions and exact pricing.
What's Included
- 11 hours on-demand video
- 24 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
Generative AI
Generative AI is the market's name for models whose output is a piece of content, such as text, images, audio, video or code, as opposed to the much larger body of models that sort, score or forecast things that already exist.
Large Language Models
Large language models are neural networks trained on a vast quantity of written text to predict the piece of text that comes next, an objective narrow enough to state in a line and broad enough to yield writing, translation, code and summary as side effects.
Transformers
A transformer is a neural-network design that takes a whole sequence in at once and, for every element in it, works out how strongly each of the other elements should influence that one.
SQL
SQL is the declarative language for asking questions of relational databases: you state which rows and columns you want and how tables relate, and the database engine works out how to retrieve them.
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.
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.
