97 Building a Needs-based Curriculum in Data Science and Artificial Intelligence: Case Studies in Indonesia, Sri Lanka, and Thailand Chutiporn Anutariya 1 , Marcello Bonsangue 2 , Taufik F. Abidin 3 , Matthew Dailey 1 , Katerina Fraidaki 4 , Tiago Gomes 6 , Felienne Hermans 2 , Suratsavadee Korkua 5 , João L. Monteiro 6 , Nugraha P. Utama 7 , Sofia Pereira 6 , Amalka Pinidiyaarachchi 8 , Sandro Pinto 6 , Jan N. van Rijn 2 , Opim Salim Sitompul 9 , Wararat Songpan 10 , Chitsutha Soomlek 10 , Frank Takes 2 , Suzan Verberne 2 , and Chitraka Wickramarachchi 11 1 Asian Institute of Technology, Thailand 2 Leiden University, the Netherlands 3 Universitas Syiah Kuala, Indonesia 4 Athens University of Economics and Business, Greece 5 Walailak University, Thailand 6 University of Minho, Portugal 7 Institut Teknologi Bandung, Indonesia 8 University of Peradeniya, Sri Lanka 9 Universitas Sumatera Utara, Indonesia 10 Khon Kaen University, Thailand 11 University of Sri Jayewardenepura, Sri Lanka Email corresponding authors: chutiporn@ait.ac.th, m.m.bonsangue@liacs.leidenuniv.nl Abstract Indonesia and Thailand are middle-income countries within the South-East Asia region. They have well-established and growing higher education systems, increasingly focused on quality improvement. However, they fall behind regional leaders in educating people who design, develop, deploy and train data science and artificial intelligence (DS&AI) based technology, as evident from the technological market, regionally dominated by Singapore and Malaysia, while the region as a whole is far behind China. A similar situation holds also for Sri Lanka, in the South Asia region technologically dominated by India. In this paper, we describe the design of a master’s level curriculum in data science and artificial intelligence using European experience on building such curricula. The design of such a curriculum is a nontrivial exercise because there is a constant trade-off between having a sufficiently broad academic curriculum and adequately meeting regional needs, including those of industrial stakeholders. In fact, findings from a gap analysis and assessment of needs from three case studies in Indonesia, Sri Lanka, and Thailand comprise the most significant component of our curriculum development process. Keywords: Curriculum Design; Higher Education; Data Science; Artificial Intelligence. 1 Introduction The use of data science and artificial intelligence (DS&AI) techniques is rapidly growing in several sectors around the world, e.g., in the health care (Jiang, Jiang, Zhi, et al., 2017), transport (Abduljabbar, Dia, et al., 2019) and financial sectors (Gomber, Koch, and Siering, 2017). This revolution is accelerated by advances in data collection, storage and analysis, efficient algorithms, and an increasing computer processing power. Although the United States, China, and Europe (Carriço 2018) are the frontrunners in developing such DS&AI methods, these world-wide scientific advances also have a major impact on other countries, such as Thailand, Indonesia, and Sri Lanka. As the fields of DS&AI have the potential to contribute positively to the economic and social climate of those countries, there seems to be a great need for training professionals in this area (McKinsey Global Institute, 2017b). Thailand, Indonesia, and Sri Lanka are middle-income countries within the South-East and South Asia region. While DS&AI based technologies are gaining traction and becoming strategic priorities, these countries are still falling behind regional leaders in the technological market, such as Singapore and Malaysia, while the region as a whole is far behind China (McKinsey Global Institute, 2017a). Thailand, Indonesia, and Sri Lanka