Public policy analysis for digital transformation
Registration Opened,
02 Jun 2026 - 01 Sep 2026
Event dates
14 Sep 2026 - 21 Oct 2026
Location
Global or multi-regional
Training topics
Big data and statistics
Digital transformation
Training type
Online instructor led
Languages
English
Coordinators
- Mindel van de Laar
- Hailey Halligan
Course level
Introductory
Duration
50 hours
Payment methods
- Bank transfer
Event email contact
Event Organizer(s)
Description
There is growing recognition that relevant, evidence-based digital policy making is key to achieving significant and sustainable change and fulfillment of the Sustainable Development Goals. In this course, you will be introduced to the fundamentals of public policy analysis tools used commonly throughout the world. Monitoring and evaluation of policies and projects is often required by international organizations, NGOs, and national governments to produce meaningful, rigorous, evidence-based recommendations based on the outcomes of existing programmes, as well as an essential part of accountability to donors and affected populations. It is therefore imperative for anyone interested in the realm of public policy for digital technology to have a grasp of what it means to conduct rigorous evaluations.
The course is divided into four units. The first unit is an introduction to public policy analysis. In the second unit students are introduced in greater detail to the monitoring process and relevant tools. Units three and four are dedicated to the description of impact evaluation methods and their practical application with cases related to digitalisation
Tutors
Hailey Halligan
Programme Coordinator, UNU Merit
Karthika Baby Sujatha
PhD Fellow, UNU-MERIT
Registration information
Document on registration information (English)
Unless specified otherwise, all ITU Academy training courses are open to all interested professionals, irrespective of their race, ethnicity, age, gender, religion, economic status and other diverse backgrounds. We strongly encourage registrations from female participants, and participants from developing countries. This includes least developed countries, small island developing states and landlocked developing countries.