COURSE OBJECTIVES
Working with data is an integral part of daily life in this technological age. The volume and rate at which data is generated necessitates powerful tools to streamline processing, inform decisions and guide our actions. It is essential for us to know a broad range of tools that are available at our disposal, so that we can expand our data analysis toolkit, and can work more effectively and collaboratively with others across various platforms to extract insights from data.
This programme introduces participants to the use of the R and Python programming languages, as well as Microsoft’s Power BI, for data science. Specifically, we will look at how these tools can help us extract and process data from various sources, perform statistical analysis, carry out predictive modeling and build machine learning models. It assumes no prior knowledge of programming, and will start with a discussion of basic concepts such as variable types, control flow, and data structures. Subsequently, we will review how to work with various data sources, from excel to databases to web-scraping, and how to carry out exploratory data analysis. Finally, we will look at the use of R, Python and Power BI for plotting/charting, making statistical inferences and predictions, as well as developing supervised and unsupervised learning models. Beyond the abovementioned topics, emphasis will also be made on good programming practices, and thoughtful application of the various tools.
Who Should Attend
Undergraduate students from any disciplines.
Pre-Requisites
Participants are expected to be able to read, write and communicate in English, as the programme will be conducted in English.
There are no subject-matter specific pre-requisites.
Programme Schedule
For individuals interested in NUS SCALE Youth programmes, please click here to enquire.
For schools/companies interested in customised and/or group bookings, please click here.
Mode of Delivery
On Campus.
Mode of Assessment
Students will be assessed via a variety of assignments and assessments:
- Continuous Assessment: Quiz
- Final Assessment: Group project
Dr Edmund Low,
Senior Lecturer, NUS College
Dr Edmund Low is a senior lecturer with the University Scholars Programme (USP) at the National University of Singapore. He has more than 14 years of academic and professional experience in the use of data-driven tools to answer questions in public health and the environment. His past projects include the use of programming and visual libraries to develop simulation models for automating workflow processes, and the setting up of remote environmental sensing systems to automate real-time continuous monitoring, for early incident warning.
He currently heads the quantitative reasoning domain, and is also director of the Quantitative Reasoning Centre, at USP. As an educator, Edmund has received both the USP Teaching Excellence Award, as well as the NUS Annual Teaching Excellence Award. Edmund holds a PhD in Environmental Engineering from Yale University.
Certificate of Completion
Successful participants who fulfill all program requirements, including meeting the minimum attendance and passing the assessment, will be awarded an e-Certificate of Completion and Assessment Report issued by NUS SCALE.