CGB organises virtual workshop on knowledge transfer
<p>Doha, Qatar: The Institute of Public Administration at the Civil Service and Government Development Bureau (CGB) organised a virtual workshop titled “Knowledge Transfer Programme: From Learning to Application, and From Knowledge to Impact.”</p> <p>The workshop was held within a collaborative framework with the Institute of Public Administration in the Kingdom of Saudi Arabia and brought…
Doha, Qatar: The Institute of Public Administration, part of the Civil Service and Government Development Bureau (CGB), recently organized a virtual workshop focused on knowledge transfer. This program connects promising government employees with private-sector and governmental institutions for a six-month professional experience.
Collaborating with the Institute of Public Administration in Saudi Arabia, the workshop attracted participants from the Gulf Cooperation Council (GCC) countries. It aimed to equip these individuals with advanced skills and best practices, which they would then apply in their government roles.
The Knowledge Transfer Programme is a key component of CGB's strategy to enhance national capacity and performance in the public sector. By exposing participants to real-world projects, mentorship, and practical skills in various areas, the programme bridges the gap between academic learning and practical application.
The virtual gathering underscored the importance of translating knowledge into tangible impact and the benefits of regional cooperation in knowledge sharing. Participants learned how Qatar's model fosters human capital development and how similar initiatives can be adapted to various national contexts.
Aligned with Qatar National Vision 2030, which emphasizes the development of a skilled workforce, the CGB remains committed to expanding the Knowledge Transfer Programme and other initiatives that strengthen the capabilities of government employees across Qatar and the broader Gulf region.
Written by urgent.news from The Peninsula Qatar's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.