AFRICAST 2026 · Forecasting for Social Good
Tidy time series & forecasting in R
Held online, 19–23 October 2026 · Recordings now available
Thank you
AFRICAST 2026 has concluded. Thank you to everyone who joined us over the week, and to the many people who made it happen: the educators, the mentors who supported learners through the exercises, our coordinator Henry Kissinger Ochieng, and the organisations that supported the training.
Recordings of every day are available in the AFRICAST 2026 YouTube playlist. You can also open the Recording & code link for each day in the sessions grid to watch that day’s sessions and get the demo code. All slides and exercises remain available, so you can keep working through the material at your own pace.
About AFRICAST
AFRICAST is part of the Forecasting for Social Good (F4SG) initiative, building forecasting skills among researchers in Low- and Middle-Income Countries so that forecasts can inform planning and resource allocation. No prior experience with time series is needed.
The training covers how to:
- Prepare time series data for analysis and exploration.
- Extract and compute useful features from time series data and visualise them effectively.
- Identify appropriate forecasting algorithms and select the best approach for the data at hand.
Sessions
Each day had two 90-minute live sessions, then exercises with mentors in the afternoon. Every day’s recording and demo code are linked under Recording & code.
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Educators
Before you start
You should be comfortable writing R code with tidyverse packages such as dplyr and ggplot2 (if not, work through https://startr.numbat.space/ first). Some familiarity with the mean, variance, quantiles, the normal distribution and regression will help, but isn’t required. To follow along with the recordings and exercises, set up the following on your own computer.
Install R and an IDE
A recent version of R (4.1+) and an IDE such as RStudio or Positron.
Install the packages
install.packages(c("tidyverse", "fpp3", "GGally", "ggtime", "astsa", "usethis"))Download the exercises
usethis::use_course("https://workshop.f4sg.org/africast/exercises.zip")Supported by
