Introduction to Machine Learning (IMLR04)
Master Machine Learning with hands‑on training in R and RStudio
https://www.prstats.org/course/introduction-to-machine-learning-imlr04/
Unlock your analytical potential in a five‑day live online course, tailored for data‑savvy researchers, analysts, and scientists. Learn how to build, evaluate, and interpret both supervised and unsupervised machine learning models using R.
Join live online sessions from wherever you are (UK time zone schedule). The course will be recorded and the sessions will be made available the same day to allow people from different time zones to follow.
Course Dates & Format
Next Session: October 6–10, 2025 (Monday to Friday)
Schedule: 8 hours per day — live online, scheduled in UK (Western European) time zone
Location: Delivered remotely across the United Kingdom, accessible worldwide through a live online platform.
Target Audience & Outcomes
Designed for applied researchers, ecologists, statisticians, analysts, and anyone comfortable with R and basic statistics. By course end you will be able to:
Implement classification, regression, and clustering algorithms
Tune models effectively and evaluate performance metrics
Apply techniques for model interpretation, including variable importance and diagnostics
Confidently choose and customise ML workflows using R tools—perfect for research or real‑world decision‑making
Fees & Registration
Early-bird rate: £400 (first 10 spots)
Standard rate: £450
Course Logistics Breakdown
Component Details Daily schedule 8 hours/day live sessions — full interactive learning Platform Real-time virtual classroom; lectures, coding, Q&A Software needed R and RStudio (instructions provided in advance) Materials Lecture slides, sample datasets, exercises & code snippets Format Hands-on practice with real-world datasets Participants should have a working knowledge of R and basic statistics (linear algebra and probability). All materials are provided, but you’ll need to install R/RStudio ahead of time.
Why Choose IMLR04?
Balanced theory + practice: Skip long lectures—focus on building real models immediately
Expert instruction: Learn from experienced tutors with deep knowledge of ML in applied settings
Collaborative learning: Join a cohort of peers, with live Q&A and group engagement
Practical relevance: Covering model tuning, evaluation, ensemble methods, unsupervised learning, and interpretability—all in R
How to Register
Visit the PR Stats course page for IMLR04
Choose early-bird (£400) or standard (£450) registration
Receive joining instructions, schedule, and software setup guide
Join live online sessions from wherever you are (UK time zone schedule). The course will be recorded and the sessions will be made available the same day to allow people from different time zones to follow.
Ready to build predictive models, interpret them effectively, and elevate your data-driven decision-making?
Email oliver@prstat.org with any questions
