Course Roadmap

This course is self-paced – there’s no fixed timetable. The roadmap below shows the suggested order, how long each session takes, and what you’ll be able to do once you finish it.

flowchart TD
    Start(["Start here"]) --> M1

    subgraph M1["Module 1 — Getting Started"]
        direction LR
        S1["1. Overview of R & RStudio"] --> S2["2. Basic R Syntax & Operations"] --> S3["3. R Markdown Basics"]
    end

    M1 --> M2

    subgraph M2["Module 2 — Working with Data"]
        direction LR
        S4["4. Vectors & Factors"] --> S5["5. Data Frames & Lists"] --> S6["6. Packages & Libraries"]
    end

    M2 --> M3

    subgraph M3["Module 3 — Data in Action"]
        direction LR
        S7["7. Basic Data Import"] --> S8["8. Basic Data Visualization"] --> S9["9. Help & Documentation"]
    end

    M3 --> Finish(["You're done!"])

Tip

Already comfortable with some of this? It’s fine to skim rather than read every word – but try not to skip Module 1 entirely. Session 3 walks you through creating the workbook.Rmd file that every later session assumes you already have open.

Module 1 – Getting Started

#	Session	Estimated time	What you’ll be able to do
1	Overview of R and RStudio	~45 min	Install R and RStudio, and find your way around the RStudio interface.
2	Basic R Syntax and Operations	~45 min	Do arithmetic in R, create and reassign variables, and identify R’s basic data types.
3	R Markdown Basics	~30 min	Create an organised R Markdown workbook to write and run your code.

Module 1 reflection checkpoint: Pause & Reflect after Module 1

Module 2 – Working with Data

#	Session	Estimated time	What you’ll be able to do
4	Vectors and Factors	~45 min	Create, access, and modify vectors; explain what factors and levels are.
5	Data Frames and Lists	~45 min	Build and modify data frames, subset rows, and work with lists and nested lists.
6	R Packages and Libraries	~30 min	Install, load, and explore R packages from CRAN and other sources.

Module 2 reflection checkpoint: Pause & Reflect after Module 2

Module 3 – Data in Action

#	Session	Estimated time	What you’ll be able to do
7	Basic Data Import	~60 min	Import data from a file or the web, and explore its structure.
8	Basic Data Visualization	~45 min	Create and customise plots with `ggplot2`.
9	Help and Documentation	~15 min	Find and read R’s built-in help files when you get stuck.

Module 3 reflection checkpoint: Pause & Reflect after Module 3

Pacing Ideas

The estimates above (~6 hours total) cover reading and following along. Add extra time for exercises and the self-check questions – most learners spend 6-9 hours on the whole course. Some ways to spread that out:

Pick a pace that suits you

Sprint – two focused days, e.g. Module 1 + 2 on day one, Module 3 on day two. Good if you’ve set aside dedicated training time.
Steady – one session per working day, finishing in under two weeks.
Casual – one session per week. If you take this route, skim the “Summary & Self-Check” of the previous session before starting the next one to refresh your memory.

Whichever pace you choose, finish each session’s Summary & Self-Check before moving on – it’s the quickest way to confirm the ideas have landed.