STATISTICAL DATA SCIENCE

Queensland University of Technology
12 JULY – 23 JULY

Statistical Data Science

Managers, practitioners and researchers are, now more than ever, interested in extracting knowledge from data. However, as our appetite for answering more challenging questions grows, so does the complexity of the corresponding data analytics. Modern applications involving big data and/or complex mathematical models motivate the development of innovative data-focussed solutions that exploit the strengths of several quantitative fields, such as mathematics, statistics, machine learning and computer science. Data science is a broad term that encapsulates the use of at least one, often multiple, of these disciplines for solving problems informed by data.

The focus of this Winter School is on data science, skewed towards methods on the statistical side of the spectrum, but where skills in modern computing, machine learning and/or mathematics remain crucial. Attendees will learn about methods for fitting complex mathematical models to data, and extracting insight from big and challenging data sets. Specifically, the School will feature modules on Bayesian statistics, advanced Markov chain Monte Carlo methods, likelihood-free inference, dimension reduction for high dimensional data, and neural networks and related models.

Program

Hosted over two weeks, this program offers a range of specialist topics with overarching themes including Bayesian statistics, advanced Markov Chain Monte Carlo methods, likelihood-free inference, modern neural networks and dimension reduction for high dimensional data.

This year’s impressive expert speaker line-up draws upon the knowledge of national lecturers at the forefront of their fields, and attracts students from all round Australia and overseas.

To maximise the experience, the school aims to feature prominent domestic speakers, researchers and lecturers as well as a number of program extras including social events, a special guest public lecture and a diversity in STEM panel event.

TOPICS INCLUDE


An introduction to Bayesian Statistics

Professor Gael Martin, Monash University



Neural Networks and Related Models

Dr Susan Wei, The University of Melbourne
Dr Robert Salomone, QUT Centre for Data Science



Post-Processing of MCMC

Dr Leah South, Queensland University of Technology

Winter School Scholarships

AMSI offers financial assistance for students and attendees from AMSI member institutions. Students looking to attend are encouraged to apply for an AMSI Scholarship to cover the cost of the program fees.

Key Dates

Apr
21
Program and scholarship applications open
May
30
Scholarship applications close (midnight)
June
04
Scholarship applicants advised of funding outcomes
June
07
Deadline for applicants to accept scholarship offers
Jun
20
Program applications close (midnight)
Jun
25
All students advised of admission into the program
Jul
12
2021 Winter School commences
Jul
23
2021 Winter School concludes

Sponsors

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