This course is an advanced course in data visualization, conceived as an extension of SIAP’s facilitated course “Data Visualization for Official Statistics and SDG Indicators,” last conducted in 2024, or, alternatively, of the self-paced course “Principles of Data Visualization for Official Statistics and SDG Indicators,” available on SIAP’s e-learning platform.
This advanced course focuses on methods for producing high-quality graphics for monitoring and publishing official statistics and SDG indicators. It highlights advanced topics in data visualization such as visualizing and representing high-dimensional datasets, visualizing uncertainty, and visualizing networks, among others. It also addresses important issues such as gender and ethical considerations in graphical communication. Additionally, the course proposes resources and practical insights on storytelling and the construction of visual narratives for diverse audiences, promoting inclusive data visualization.
This course is at an advanced level, participants must have successfully completed one of these courses prior to registration :
- “Data Visualization for Official Statistics and SDG Indicators” a facilitated course last conducted in 2024, or, alternatively,
- “Principles of Data Visualization for Official Statistics and SDG Indicators” a self-paced course available on SIAP’s LMS.
This Self-paced e-learning course aims to build capacity in statistical offices for the development of Reproducible Analytical Pipelines (RAPs). This course has a practical goal, participants should have some experience in R programming (see the flyer).
Completing a mandatory tutorial is required for participants to complete before being able to access to the 4 modules of the course.
Developed with the support of Vanuatu Bureau of Statistics (VBoS).
This course introduces data visualization as a tool to produce high-quality graphics for monitoring official statistics and the Sustainable Development Goals (SDGs) indicators.
The course is not based, nor does it focus, on any software. However, some popular software will be introduced and used in the course (Excel, QGIS, R/Rstudio, R Shiny, Google Sheets) as well as references to online tools.
See the flyer and the concept note
-- A facilitated course is organized from 11 August - 26 September --
Enrolment to this self-paced course is paused during that period.
Come join the facilitated course!
The course aims at providing an overview of the current methods and applications of Machine Learning, through theoretical concepts, pedagogical case studies and interactive resources. The course is not based on, nor does it require, a particular software. However reproducible examples are provided using the R/RStudio environment and Python.
See the flyer and the concept note
Unlock the Power of Data with the Asia-Pacific Data Masterclass!
Are you a senior leader looking to make better decisions? Or are you a statistician looking to refresh your data skills? Join the Asia-Pacific Data Masterclass, specifically designed for non-analytical leaders across Asia and the Pacific.
This course will empower you to:
- Integrate data and evidence into the heart of your decision-making;
- Foster a data-driven culture in your organization;
- Harness data to shape policy and enhance communication; and
- Apply cutting-edge data science for more impact.
Elevate your leadership and drive innovation in your organization. Don't miss this opportunity to master the art of data!
As part of their project on Big Data for Official Statistics, ESCAP, together with DESA Statistics Division (UNSD) and UNICEF South Asia, are providing capacity support to invited countries that have indicated the use of earth observation data with SAE as a priority. This support includes this facilitated e-learning course on SAE, which will take place during July-September 2024, and an in-person workshop relating to the use of EO data for SAE, to be held in Bangkok, Thailand between 21 and 25 October 2024.
The facilitated e-leaning is based upon a course developed by UNSD, ECLAC Statistics Division and UNFPA to cover the foundational knowledge of small area estimation (SAE) techniques and skills necessary for participants to apply these models in their data analysis work.
As part of the fourteenth tranche of the UN Development Account project on Statistics and Data themed on enhancing the resilience and agility of NSSs to respond to emerging economic, social and environmental data needs in times of crises and disasters, the Economic Commission for Africa (ECA) together with the United Nations Statistics Division (UNSD) of DESA are providing capacity support to invited African countries.
In line with the project's goal developing and encouraging the use of innovative data sources and collection methods supported by adequate governance mechanisms and modern technologies while ensuring a path towards achieving the 2030 Agenda; this guided eLearning course on SAE, which will run August to September 2024, has been offered to key technical staff from NSOs in Africa.
The guided eLearning is based upon a course developed by UNSD, ECLAC's Statistics Division and UNFPA to cover the foundational knowledge of small area estimation (SAE) techniques and skills necessary for participants to apply these models in their data analysis work.