Course Reference No: TGS-2020513882 (Classroom Learning)
This course is aligned with the Infocomm Technology Skills Framework for Data Analyst and Data Scientist and will use R, a widely used statistical package. The course aims to quickly bring up to speed a programmer or business analyst who already knows how to programme in other language or have done advanced Excel macros to begin using R as a data science tool.
The course will define data science and explore the first two things a data scientist must do – cleaning and visualising data. You will learn and use R's dplyr, ggplot and ggvis packages for these tasks. It will then cover the Data Science Workflow – training models and testing them through the application of machine learning models to various industry-relevant data science problems. The tool used will be the Caret package.
At the end of the course, participants should have a working knowledge of how to solve data science problems with R and the following:
27 and 28 July 2023
Location for 27th July 2023 is L1-S2, Level 1 Academia
Location for 28th July 2023 is AC6-3 meeting room, level 6 Academia
39 years old or younger
Dr Chia Hui Teng
Chia Hui Teng is a senior lecturer with the Department of Statistics and Data Science, National University of Singapore.
Hui Teng is an experienced educator with close to two decades of teaching experience at institutions of higher learning. Her area of expertise is in Statistics and Analytics education where she supports the upskilling of working adults and students in data competencies. Hui Teng serves as an advisor in curriculum design and professional development, spearheaded various projects as well as conducted workshops in the area of statistics and visual analytics. Her contributions in helping to prepare graduates for a data-centric workforce received national recognition. She won the President's Award for Teachers, which is the highest accolade for the teaching profession in Singapore.
Hui Teng holds a PhD from the National Institute of Education, Nanyang Technological University. Her research interests are in sense-making, visual analytics and statistical literacy.
Dr Ning Yilin
Ning Yilin is a research fellow with the Centre for Quantitative Medicine, Duke-NUS Medical School. Her expertise is in the development of biostatistical and machine learning methods for healthcare applications. She has published research papers in top-tier journals, including Patterns (published by Cell Press) and eClinicalMedicine (published by The Lancet), and received the Khoo Postdoctoral Fellowship Award in 2021. As a researcher, Yilin is experienced in data analysis using R, and has published two R packages and one R Shiny application. She had teaching experience as a lecturer for an introductory course on R programing for medical students. Yilin holds a PhD from the NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore.
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