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Work confidently with big data in R

Most R users hit a wall when their data grows past a few million rows. Spreadsheets lock up, CSVs take forever to load, and analyses grind to a halt. Proprietary tools promise speed but come with cost and lock-in. This course shows you how to handle big data in R using open, modern tools.

What you'll learn

  • Analyse larger-than-memory data: Use Arrow with dplyr to query millions of rows without crashing R.

  • Streamline data storage: Convert messy CSVs into space-saving, shareable Parquet files.

  • Boost performance: Optimise Arrow datasets to take full advantage of your hardware.

  • Stay open-source: Learn solutions that avoid expensive licenses and vendor lock-in.

  • Build reproducible workflows: Standardise on formats and tools designed for long-term reliability.

Bonus material

  • Early Bird Discount

    $50 value

    Save when you sign up early; founding students get access at a reduced rate as thanks for being part of the first cohort.

  • Exclusive Q&A Session

    $97 value

    Direct support from the instructor; get a chance to bring your own data questions and challenges to a live session.