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R Programming Language Data & Analytics

R Programming Language

R is purpose-built for statistics and data analysis, and it's a core tool in research and analytics. This course covers R programming, working with data frames, statistical analysis and creating visualisations. It's ideal for anyone heading into data analysis, research or academic work that needs real statistical power.

Duration
1.5 Months
Format
Live 1-on-1
Level
Professional
Certificate
Osian
Overview

What this course is about

Osian Academy teaches R Programming Language through live one-on-one online classes built around clear explanations and practical work. You will study r syntax, vectors, data frames, tidy data, dplyr, ggplot2, functions, imports, missing values, descriptive statistics and basic modelling concepts. This R Programming Language pathway gives that point a course-specific practice focus, reference 211-20. This R Programming Language pathway gives that point a course-specific practice focus, reference 211-20. This R Programming Language pathway gives that point a course-specific practice focus, reference 211-20.

Practice centres on an analysis report built from a cleaned dataset with charts, summary tables, interpretation and an R Markdown workflow. This R Programming Language pathway gives that point a course-specific practice focus, reference 211-20. The lessons use r, rstudio, tidyverse packages, sample csv files and a laptop; package versions should be checked before practice, with version or access checks discussed before setup. This R Programming Language pathway gives that point a course-specific practice focus, reference 211-20.

This course is especially useful when you want data cleaning, exploratory analysis, visualisation, interpretation and reproducible reporting. It is distinct from a python data course, this course uses r syntax, tidyverse workflows and r markdown for statistical reporting, because the lessons here prioritise the tools, vocabulary and practical decisions specific to r programming language. This R Programming Language pathway gives that point a course-specific practice focus, reference 211-20.

By the end

What you’ll be able to do

  • Explain the core ideas behind r programming language using accurate terminology
  • Set up and use the main tools for r programming language practice
  • Apply r syntax in a guided practical task
  • Build and review an analysis report built from a cleaned dataset
  • Practise R Programming Language in a guided task, course note 211-20.
  • Present a portfolio or study outcome relevant to r data analyst support and research reporting
Syllabus

How the course flows

  1. 1
    Data FoundationsWeek 1

    Data types, spreadsheets and thinking analytically.

  2. 2
    Querying & WranglingWeek 2

    Pulling and cleaning data with SQL and tools.

  3. 3
    VisualisationWeek 3

    Dashboards in Power BI / Tableau that tell a story.

  4. 4
    Statistics & InsightWeek 4

    Core statistics and drawing sound conclusions.

  5. 5
    Analytics ProjectWeeks 5–6

    An end-to-end analysis on a real dataset.

Toolkit

Tools you’ll use

  • Excel
  • SQL
  • Power BI
  • Tableau
  • Python (pandas)
Audience

Who this course is for

  • Beginners seeking r programming language classes with a personal teacher
  • Learners selecting R Programming Language for a focused pathway, group 211-20.
  • Learners selecting R Programming Language for a focused pathway, group 211-20.
  • Learners selecting R Programming Language for a focused pathway, group 211-20.
  • Learners selecting R Programming Language for a focused pathway, group 211-20.
Where it leads

Roles this opens up

  • R Data Analyst

    Use r programming language knowledge to support practical tasks, projects and continued skill development.

  • Research Data Assistant

    Contribute to an analysis report built from a cleaned dataset with charts, summary tables, interpretation and an r markdown workflow under the guidance of a senior practitioner or team.

  • Statistical Reporting Assistant

    Apply the course workflow in documentation, troubleshooting and day-to-day delivery settings.

Questions

Before you enrol

Basic mathematics and spreadsheet familiarity are useful, while programming beginners can learn R syntax through guided examples. This R Programming Language pathway addresses that point through guided practice, reference 211-20.

Plan to use R, RStudio, tidyverse packages, sample CSV files and a laptop; package versions should be checked before practice. This R Programming Language pathway addresses that point through guided practice, reference 211-20.

A central exercise is an analysis report built from a cleaned dataset with charts, summary tables, interpretation and an R Markdown workflow. This R Programming Language pathway addresses that point through guided practice, reference 211-20.

It develops data cleaning, exploratory analysis, visualisation, interpretation and reproducible reporting through demonstrations, practice and feedback. This R Programming Language pathway addresses that point through guided practice, reference 211-20.

Compared with a Python data course, this course uses R syntax, tidyverse workflows and R Markdown for statistical reporting, this course gives priority to r syntax, vectors, data frames, tidy data, dplyr, ggplot2, functions, imports, missing values, descriptive statistics and basic modelling concepts.. This R Programming Language pathway addresses that point through guided practice, reference 211-20.

This R Programming Language pathway addresses that point through guided practice, reference 211-20. This R Programming Language pathway addresses that point through guided practice, reference 211-20.