Hansila Sudasinghe
Hansila Sudasinghe is a dedicated data science professional and educator with a robust background in computing and information systems. She completed her Master of Data Analytics at the Faculty of Graduate Studies, University of Kelaniya, following a Post-Graduate Diploma in Information Technology from the University of Colombo School of Computing. Hansila holds a B.Sc. (special) in Computing & Information Systems from Sabaragamuwa University of Sri Lanka, where she graduated.
With extensive teaching experience across various academic institutions, Hansila currently working as a Lecturer in Computer Science at the Edith Cowan University – Sri Lanka Campus. She has completed a Certificate Course in Teaching in Higher Education and earned badges for her contributions to professional development. Hansila is actively involved in curriculum development and research, contributing to projects that integrate technology and data science with practical applications.
Her expertise spans multiple programming languages and tools, including Python, SQL, Java, and Power BI, with a focus on data analysis, web development, and business intelligence. Recent projects include analyzing social media sentiments on global economic issues and developing data-driven solutions for the apparel industry. She has also co-authored research on topics ranging from obesity prediction models to mobile banking adoption.
An advocate for continuous learning and collaboration, Hansila has actively participated in workshops, technical committees, and community events. She aims to bridge the gap between academia and industry by equipping students and professionals with the skills needed to thrive in a data-driven world.
Sessions
This proposal aims to develop a Python curriculum for data science for multidisciplinary studies in university education. Data Science is nowadays a trending topic in any area like social science, finance, natural science and so many others. Therefore, every student in the university education is keen to learn data science using computer languages rather than using SPSS or other traditional data analysis tools especially related to research. So, this aims to develop a new curriculum for any student studying from any discipline in higher education to learn data science using trending techniques and tools. Python is the core programming language here because it is very widely used and related to data science field. Plus, it has many advantages like easy to learn and use, platform independence used, large and active community support. Utilizing Bloom’s Taxonomy as the guiding framework has developed a new curriculum for four-year degree programs to succeed in data driven world considering multidisciplinary approach. In this curriculum, students can start from Python basic programming concepts to progress to advanced analyzing techniques using libraries like Pandas, NumPy, and Seaborn, and platforms such as Anaconda and Google Colab and finally build own projects in that students related discipline. Ultimately this curriculum will leverage success in Data-centric society in domain specific applications.
Keywords: Bloom’s, curriculum, multidisciplinary, python, science, taxonomy