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PeDaS 2025 · Data Science Education
Building Forecasting Skills through the PeDaS 2025 Workshop Programme
A three-day online learning programme on time series forecasting, connecting data science concepts with an Indonesian automotive industry challenge.
Pesta Data Nasional (PeDaS) 2025, organised through a collaboration between APTIKOM and UIN Syarif Hidayatullah Jakarta, incorporated a workshop programme into its national data science activities. The published schedule set the workshops for 27–29 August 2025, focusing on forecasting approaches relevant to analysing changes over time.
Programme at a glance
- Organisers
- APTIKOM and UIN Syarif Hidayatullah Jakarta
- Published workshop dates and format
- 27–29 August 2025 · Online · Three days
- Learning focus
- Univariate, multivariate, and multiple time series forecasting
- Published programme audience
- Active D3, D4, and undergraduate (S1) students; the national competition invited teams from institutions across Indonesia.
A structured introduction to forecasting
The published workshop outline organised learning into three stages, with contributions planned from academic and industry speakers:
- Day 1 — Univariate time series forecasting: foundational approaches to forecasting a single time-dependent series.
- Day 2 — Multivariate time series forecasting: an introduction to forecasting involving several variables.
- Day 3 — Multiple time series forecasting: concepts and implementation for working with multiple series.
The wider programme connected these topics with the challenge of predicting automotive trends in Indonesia. Its competition used vehicle sales data from GAIKINDO, providing an applied context for developing forecasting models.
Relevance to SDG 4: Quality Education
The workshop’s emphasis on applied analytical skills is relevant to SDG 4’s focus on education and skills development. Its national scope created a learning opportunity extending beyond a single institution. Assessing its eligibility as evidence of publicly accessible vocational training requires confirmation of the workshop’s own admission arrangements, separately from the competition’s student eligibility rules.
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