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    • R

    R Courses Online

    Master R programming for statistical computing and data analysis. Learn about R syntax, data manipulation, and visualization techniques.

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    Explore the R Course Catalog

    • U

      University of Colorado System

      Clinical Natural Language Processing

      Skills you'll gain: Natural Language Processing, Text Mining, Clinical Data Management, R Programming, Google Cloud Platform, Health Informatics, Unstructured Data

      3.7
      Rating, 3.7 out of 5 stars
      ·
      23 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free
      Free
      C

      Coursera Instructor Network

      Introduction to Retrieval Augmented Generation (RAG)

      Skills you'll gain: Prompt Engineering, Large Language Modeling, ChatGPT, OpenAI, Generative AI, Artificial Intelligence and Machine Learning (AI/ML), Natural Language Processing, Application Development, Data Store, Data Storage Technologies

      4.2
      Rating, 4.2 out of 5 stars
      ·
      10 reviews

      Beginner · Course · 1 - 4 Weeks

    • F

      Fred Hutchinson Cancer Center

      Researcher's Guide to Omic Data

      Skills you'll gain: Bioinformatics, Molecular Biology, Data Processing, Data Analysis, Data Literacy, Research Design, Exploratory Data Analysis, Metadata Management, Experimentation, Science and Research, R Programming, Scientific Methods, Spatial Analysis, Data Collection, Data Quality, Data Validation, Quantitative Research, Biology, Qualitative Research, Analysis

      3.8
      Rating, 3.8 out of 5 stars
      ·
      22 reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      Interacting with the System and Managing Memory

      Skills you'll gain: Maintainability, Program Development, C (Programming Language), Software Engineering, System Programming, Programming Principles, Software Development, Simulations, Command-Line Interface, Operating Systems, User Interface (UI), Data Structures, Debugging, Data Import/Export, File Management

      4.3
      Rating, 4.3 out of 5 stars
      ·
      173 reviews

      Beginner · Course · 1 - 4 Weeks

    • E

      EDUCBA

      Embedded Systems using C

      Skills you'll gain: C (Programming Language), Embedded Systems, Embedded Software, Debugging, System Programming, Microarchitecture, Computer Architecture, Data Structures, Computer Hardware, Peripheral Devices

      3.8
      Rating, 3.8 out of 5 stars
      ·
      66 reviews

      Beginner · Course · 1 - 4 Weeks

    • B

      Board Infinity

      Backend Development for .Net Full Stack

      Skills you'll gain: Model View Controller, ASP.NET, Restful API, .NET Framework, JSON, Web Services, Web Applications, Application Programming Interface (API), Back-End Web Development, Software Architecture, Application Security, Object-Relational Mapping, Extensible Markup Language (XML), Authentications, Authorization (Computing)

      3.8
      Rating, 3.8 out of 5 stars
      ·
      38 reviews

      Intermediate · Course · 1 - 4 Weeks

    • L

      LearnQuest

      Data Processing with Azure

      Skills you'll gain: Microsoft Azure, Big Data, Data Processing, Analytics, Data Pipelines, Databricks, Apache Spark, PySpark, Data Analysis, Data Warehousing, Extract, Transform, Load, Real Time Data, Data Transformation, Scheduling, Data Storage

      3.7
      Rating, 3.7 out of 5 stars
      ·
      67 reviews

      Intermediate · Course · 1 - 3 Months

    • S

      SkillUp EdTech

      ASQ-Certified Six Sigma Black Belt (CSSBB) Exam Prep

      Skills you'll gain: Statistical Process Controls, Statistical Hypothesis Testing, Lean Methodologies, Team Motivation, Process Improvement, Six Sigma Methodology, Kaizen Methodology, Process Capability, Risk Analysis, Team Leadership, Quality Improvement, Team Management, Benchmarking, Performance Measurement, Change Management, Process Analysis, Statistical Analysis, Continuous Improvement Process, Organizational Change, Team Building

      4.8
      Rating, 4.8 out of 5 stars
      ·
      28 reviews

      Intermediate · Specialization · 1 - 3 Months

    • A

      Amazon Web Services

      Capstone: Following the AWS Well Architected Framework

      Skills you'll gain: Cloud Computing Architecture, Amazon Web Services, Cloud Security, Operational Excellence, Solution Architecture, Cloud-Native Computing, Corporate Sustainability, Performance Tuning, Operational Efficiency, Environmental Social And Corporate Governance (ESG), Cost Reduction, System Requirements, Cost Management, Disaster Recovery, Interviewing Skills

      4.5
      Rating, 4.5 out of 5 stars
      ·
      38 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Generalized Linear Models and Nonparametric Regression

      Skills you'll gain: Statistical Modeling, R Programming, Data Analysis, Data Ethics, Advanced Analytics, Statistical Methods, Regression Analysis, Machine Learning, Classification And Regression Tree (CART), Statistical Inference, Probability Distribution

      Build toward a degree

      4.3
      Rating, 4.3 out of 5 stars
      ·
      20 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      Universidad Austral

      Manejo de bases de datos con Python

      Skills you'll gain: Relational Databases, Object-Relational Mapping, Database Management, Database Design, SQL, Databases, Database Development, Query Languages, Data Integrity, Data Manipulation

      4.2
      Rating, 4.2 out of 5 stars
      ·
      180 reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      Dartmouth College

      C Programming: Advanced Data Types - 5

      Skills you'll gain: C (Programming Language), Embedded Systems, Data Structures, Programming Principles, Algorithms, Operating Systems, Linux, Computer Programming Tools, Debugging

      4.4
      Rating, 4.4 out of 5 stars
      ·
      55 reviews

      Beginner · Course · 1 - 3 Months

    R learners also search

    Data
    Data Analysis
    Data Science
    Data Analytics
    Analysis
    R Programming
    Beginner Data Analysis
    Beginner Data Analysis
    1…313233…48

    In summary, here are 10 of our most popular r courses

    • Clinical Natural Language Processing: University of Colorado System
    • Introduction to Retrieval Augmented Generation (RAG): Coursera Instructor Network
    • Researcher's Guide to Omic Data: Fred Hutchinson Cancer Center
    • Interacting with the System and Managing Memory: Duke University
    • Embedded Systems using C: EDUCBA
    • Backend Development for .Net Full Stack : Board Infinity
    • Data Processing with Azure: LearnQuest
    • ASQ-Certified Six Sigma Black Belt (CSSBB) Exam Prep: SkillUp EdTech
    • Capstone: Following the AWS Well Architected Framework: Amazon Web Services
    • Generalized Linear Models and Nonparametric Regression: University of Colorado Boulder

    Skills you can learn in Data Analysis

    Analytics (85)
    Big Data (64)
    Python Programming (47)
    Business Analytics (40)
    R Programming (37)
    Statistical Analysis (36)
    Sql (33)
    Data Model (29)
    Data Mining (27)
    Exploratory Data Analysis (26)
    Data Modeling (21)
    Data Manipulation (20)

    Frequently Asked Questions about R

    R programming courses on Coursera offer learners an opportunity to master a wide array of skills essential for data analysis, statistical computing, and graphical representation, including:

    • Fundamentals of R syntax and programming environment
    • Data manipulation and cleaning techniques using R packages like dplyr and tidyr
    • Statistical analysis and model building to interpret complex data sets
    • Creating compelling visualizations with ggplot2 and other visualization tools
    • Developing reproducible reports and interactive web apps with R Markdown and Shiny
    • Applying R in various domains such as finance, healthcare, and academic research ‎

    Coursera’s R programming courses are designed to welcome learners at different levels of expertise:

    • No prior programming experience is required for introductory courses, which focus on the basics of R and general programming concepts.
    • Intermediate courses are suitable for learners with some programming background, enhancing their data manipulation and analysis skills.
    • Advanced courses cater to experienced users seeking to deepen their expertise in statistical methods, machine learning, or R package development.‎

    Coursera’s R programming courses are designed to welcome learners at different levels of expertise:

    • No prior programming experience is required for introductory courses, which focus on the basics of R and general programming concepts.
    • Intermediate courses are suitable for learners with some programming background, enhancing their data manipulation and analysis skills.
    • Advanced courses cater to experienced users seeking to deepen their expertise in statistical methods, machine learning, or R package development.‎

    Engaging in R programming courses on Coursera can lead to several forms of recognition that highlight your skills and dedication:

    • Course Certificates: These certificates demonstrate your success in individual R programming courses, showcasing your skills in specific aspects of the language.
    • Professional Certificates: Obtain these by completing a series of courses that prepare you for data analysis and statistical roles using R.
    • Specializations: Deepen your proficiency with comprehensive course sequences that focus on specific areas such as statistical analysis, machine learning, or advanced data visualization with R. ‎

    Looking to enhance your team's R programming skills? Coursera provides tailored enterprise solutions for teams ranging of 5-125 employees. Our offerings include advanced analytics, customized learning paths, and collaborative tools. To explore our R programming training options and make a purchase, please visit our Coursera for Teams page.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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