• Understand the foundations of data in development contexts.
• Navigate the development data ecosystem and governance challenges.
• Apply quantitative and qualitative methods for data collection and analysis.
• Use data visualization and storytelling techniques for decision-making and advocacy.
• Explore the potential of big data and AI for development impact.
• Develop actionable outputs such as data management plans and project-level analytics strategies.

This course introduces core concepts, methods, and tools that help development professionals use data more effectively in their daily work. Topics include:

• Data, Information, and Evidence in Development
  
  Understanding how data supports evidence-based decision-making in development programmes and projects.
• The Development Data Ecosystem
  
  An overview of common data sources, data types, quality considerations, ethics, and governance in development contexts.
• Data Collection and Management
  
  Practical approaches to collecting and organizing qualitative and quantitative data, including surveys, interviews, and administrative data.
• Introduction to Data Analytics for Development
  
  Applying basic analytical approaches to explore data, identify patterns, and support programme monitoring and evaluation.
• Qualitative and Quantitative Data Analysis
  
  Understanding how qualitative and quantitative methods can be used separately and together to generate meaningful insights.
• Data Visualization and Storytelling
  
  Learning how to present data clearly using visualizations and simple narratives tailored to different audiences.
• Big Data and New Data Sources: An Introduction
  
  Exploring emerging data sources and their potential use in development, including opportunities and limitations.
• Looking Ahead: AI and the Future of Data in Development
  
  An introductory look at how artificial intelligence and advanced analytics are influencing development practice, with attention to responsible use.

Participants who successfully complete the course will be able to:

• Better understand how data is used across the development project and programme lifecycle.
• Assess basic data needs and data gaps in their own projects or organizations.
• Design a simple data management and analysis plan for a programme or project.
• Apply quantitative and qualitative analysis techniques to real-world development data.
• Create clear and effective data visualizations to support reporting and communication.
• Use basic data storytelling techniques to explain findings to colleagues and stakeholders.
• Identify potential opportunities to use new data sources and AI-enabled tools, with a realistic understanding of their benefits and limitations.

This certification programme is delivered in a blended learning format, combining distance learning with an in-person learning experience. It includes an online phase followed by a one-week workshop in Turin at the United Nations Campus, as part of the 2026 Development Cooperation Academy.

For more information on the Academy please click on the following link 

After the workshop, participants complete a final project with remote expert support before receiving their certification.

The programme represents approximately 70 hours of learning over seven weeks and is designed to be practical and manageable alongside professional commitments.

By joining this course, you will:

• Build practical and realistic data skills that you can apply immediately in your work.
• Improve your confidence in understanding, analysing, and communicating data.
• Learn how to use data more effectively for programme planning, monitoring, reporting, and learning.
• Become familiar with current tools and emerging trends in data analytics, including big data and AI, without requiring advanced technical expertise.
• Learn alongside a diverse, international group of professionals, creating opportunities for peer learning and professional networking.

Upon successful completion of the Academy, participants receive a Certificate of Achievement in their chosen discipline.

This certificate shows that you have fulfilled all assignments, knowledge tests and other prerequisites to a minimum standard.

The complete effort amounts to 70 hours of learning.

The certificate is a digital certificate which is protected by block-chain technology and can be displayed on social media.