Graduate Certificate in Big Data Analytics in Precision Medicine
Programme Highlights
Organised by the Department of Biochemistry, the Graduate Certificate in Big Data Analytics in Precision Medicine aims to provide foundational knowledge and skills for learners to apply appropriate statistical approaches in evaluating and analysing high-throughput datasets in precision medicine.
It provides the foundational knowledge and skills for big data processing by leveraging on high performance computing resources of the National Supercomputing Centre (NSCC). Learners will be introduced to the theory and application of high-performance systems covering HPC architecture and workflows as well as approaches to accelerate analytical pipelines.
Who Should Attend
Individuals who are currently working in healthcare, research or diagnostic lab, biotechnology, pharmacology, academic medicine or education fields.
Registration Period & Course Structure
- Participants who complete the following 2 executive certificates will receive a ‘Graduate Certificate in Big Data Analytics in Precision Medicine’. For more information on the individual courses, timetable and fees, click on the course titles below.
- Participants will have to sign up for the individual academic courses under each executive certificate in the NUS Online Application portal.
- Application period for Executive Certificate in Applied Statistics for Precision Medicine: 28 Sep 2023 – 5 Nov 2023 ; Semester 2 (AY23/24) Intake.
- Application period for Executive Certificate in High Performance Computing for Precision Medicine: TBA – estimated to open in 2nd Quarter of 2024.
Dates
Certificates
15 January 2024 – 15 April 2024
(Hybrid)
Classes will be held every Monday, 2pm – 5pm.
Executive Certificate in Applied Statistics for Precision Medicine
(PHM5003: Applied Statistics for Precision Medicine course)
Dates to be advised.
Registration Period TBA (Q2 2024)
Executive Certificate in High Performance Computing for Precision Medicine
(PHM5004: High Performance Computing for Precision Medicine course)
Benefits of Attending
Learners should be able to:
- Explain principles of statistical modelling of data for precision medicine
- Explain the challenges of analyzing high throughput datasets for precision medicine
- Design high throughput experiments in precision medicine to minimize confounders and increase statistical power to detect differences
- Evaluate data quality (batch effects, missing data, noise) and perform preprocessing where appropriate (batch correction, imputation, normalization)
- Analyze high throughput data to find and evaluate differences in samples using appropriate statistical tools
- Evaluate and explain the runtime complexity of algorithms used in analysing data for precision medicine
- Describe the architecture of high-performance systems and relate it to the latencies in processing data
- Evaluate data processing workflows and identify bottlenecks using profiling methods
- Explain the different models of parallel computing
- Evaluate and identify suitable applications that utilize parallel computing for accelerating workflows
- Parallelize a high-throughput workflow and optimize the bottlenecks where necessary
- Containerize applications and binaries for reproducible computing in a shared HPC environment
Trainer Profile
For more information on the trainers’ profile, please view the respective course pages.
Minimum Entry Requirement
Applicants must have a Bachelor’s degree and may be required to show relevant work experience. Applicants with other qualifications and experience may be considered on a case by case basis, subject to approval by the school.
- Executive Certificate in Applied Statistics for Precision Medicine: Basic knowledge of R language
- Executive Certificate in High Performance Computing for Precision Medicine: Familiarity with Linux environment
Mode of Training
Hybrid mode of delivery
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