Melbourne Data Science Week - 29 May - 2nd June 2017
melbourne data science week
Tutorials
Reception
&
8 Tutorials
|
Conference
|
18 Speakers
|
2 Tracks
29 May - 2 June 2017
Sold Out Last Year!
Educational Talks
Tutorials
Networking
Interaction
Social
Tickets Now Available
71Days
3Hours
43Mins
52Secs

Melbourne Data Science Week 2017

Two sold out events from 2016 are combining in 2017 to create what will hopefully be a great Data Science-palooza for Melbourne. Learn about applications, data, ideas and the latest tools for data science. Participate in panel sessions and break-time discussions with your colleagues from industry, academia and government. Hear from the datathon winners about how they did it.
 
For those who want hands on Data Science training there will be 8 full day tutorials from Mon-Thu.
 
On Thursday evening we will kick off with 2 talks and drinks & finger food reception @ KPMG 
 
The 2 track WOMBAT MeDaScIn conference will be on Friday @ nab
 
Melbourne Data Science week and the Melbourne Datathon are co-ordinated by the DSM meetup group  for the community. The cost of this event is kept low thanks to the fantastic support we receive and any proceeds will be used to help continue organising events.
 
We thank everyone for their support and hope you enjoy the week.
 
 
 

 

 

 

 

Meet the Speakers

Click on the Speaker's photo for details

Glen Rabie

CEO at Yellowfin

Chris Culnane

Research Fellow at University of Melbourne

Lawrence Mosley

CEO at Omni Analytics Group

Lisa Schutz

Managing Director at Verifier and InFact Decisions

Graham Williams

Director of Data Science at Microsoft

Colette Marais

Data Scientist at Telstra

Ying Yang

Director of Data Science at Australian Taxation Office

Yihui Xie

Software Engineer at RStudio, Inc.

You

Datathon Winner

Ross Gayler

Independent Consultant

Di Cook

Professor of Business Analytics at Monash University

Eunkyung Lee

Chair of Statistics Department at EWHA Women’s University, Korea

Amy Shi-Nash

Head of Data Science at Commonwealth Bank of Australia

Tiberio Caetano

Chief Scientist at Ambiata

Simon Angus

Senior Lecturer at Monash University

Nick Tierney

Post-Doctoral Researcher at Monash University

Andrew Robinson

Director of CEBRA at The University of Melbourne

Diana Benavides Prado

Data Scientist at the Centre for Social Data Analytics, AUT

Stephanie Kovalchik

Data Scientist at Tennis Australia

Meet the Tutors

Click on the Tutor's photo for details

Eunkyung Lee

Chair of Statistics Department at EWHA Women’s University, Korea

Eric Hare

Data Scientist at Omni Analytics Group

Isaac Reyes

Head of Data Science at Altis Consulting

Phil Brierley

Independent Data Science Consultant

Di Cook

Professor of Business Analytics at Monash University

Nayyar Zaidi

Data Scientist and Research Fellow (Machine Learning) at Monash University

Rob Hyndman

Professor of Statistics at Monash University

Zhen He

Associate Professor at La Trobe University

Stephanie Kovalchik

Data Scientist at Tennis Australia

Graham Williams

Director of Data Science at Microsoft

Lawrence Mosley

CEO at Omni Analytics Group

Earo Wang

PhD Student at Monash University

Yihui Xie

Software Engineer at RStudio, Inc.

Yanchang Zhao

Founder of RDataMining.com

Tutorials

Click on the tutorial title for content
Day 1
29 May 2017

The Art of Data Storytelling

Prerequisites : None Requirements : Laptop with your choice of visualisation package Day Outline: I. Introduction and Ice Breaker – Let’s Tell Stories II. The Keys to Data Storytelling and...
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Isaac Reyes

Time Series in R, Forecasting and Visualisation

Prerequisites: An introductory level statistics knowledge. Basic R language programming. Requirements: Laptop loaded with latest version of R, and a selection of packages to be provided later. Workshop is hands-on....
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Earo Wang
Rob Hyndman
Day 2
30 May 2017

R Markdown Ecosystem (reports, papers, dashboards, books, websites, and presentations)

Prerequisites:  Basic R language programming. Requirements: Laptop loaded with latest version of R, and a selection of packages to be provided later. Workshop is hands-on. 1. Getting started with Rmarkdown...
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Yihui Xie

Getting Started with Deep Learning

Prerequisites:  none Requirements: laptop for laboratory Outline: Introduction Why use deep learning The basics of deep learning Convolutional neural networks and software Introduction to Convolutional Neural Networks (CNNs) State of the...
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Zhen He
Day 3
31 May 2017

Visualisation for Data Mining

Prerequisites: Experience with data mining methods such as classification trees, random forests, support vector machines. Basic R language programming. Requirements: Laptop loaded with latest version of R, and a selection...
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Di Cook
Eunkyung Lee

Getting Started with Predictive Modelling and Machine Learning

Tutorial Objective To give a general overview of the whole predictive modelling process and the issues you will need to think about for your predictive modelling projects to be successful....
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Phil Brierley
Nayyar Zaidi

Sports Analytics with R

Description: This will be a crash course on how to use R to conduct data science for sports. After this course, participants will be able to scrape sports data from...
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Stephanie Kovalchik
Day 4
01 Jun 2017

Building Web Apps and Dashboards with RStudio’s Shiny

  1. What is shiny and examples 2. Structure of a shiny ppp, server and ui 3. Inputs and outputs 4. Reactive programming, getting your plots to respond to user...
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Eric Hare
Lawrence Mosley

Machine Learning with Rattle and R

Prerequisite: Familiarity with scripting and/or programming Requirement: Laptop with latest R and Rattle and X2Go installed together with packages to be advised. The workshop is hands on. Overview: The popularity...
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Graham Williams

Datamining Applications with R

Call back later for tutorial content.
Yanchang Zhao

Highlights from 2016

Welcome Reception and Talks

Thu 1st June 2017 – 5:15pm – 8:30pm
KPMG
Tower Two Collins Square
727 Collins St
Melbourne

(all tutorials will also be held at KPMG)

Wombat MeDaScIn Conference

Friday 2nd June 2017- 8:00am onwards
nab Arena
700 Bourke St
Melbourne

The nab is on the walkway between Southern Cross Station and Etihad Stadium. For directions see here or a map here, or just scroll through the pictures below.

The Arena is on the ground level just opposite the cafe. The Hall is at the top of the escalator located in the foyer just outside the Arena.

Sponsors

Sponsorship opportunities for Melbourne Data Science Week are available. Please click here for details.

 

Extreme Gradient Boosted Sponsors



Bayesian Believers

We appreciate the continued support of DSM throughout the year by by the following companies


La Trobe University, Yellowfin, Data Science Solutions, AGL, iSelect, Teradata, Rubix Consulting, deepWhite, SAS, Monash University, KPMG, Zendesk, northraine, Sportsbet, Tiberius Data Mining, nab


 

The inaugural Melbourne Data Science Week would not have been possible without the generous support of all our tutors, speakers, hosts and sponsors – THANK YOU

 

 

 

If you would like to get involved with DSM then please let us know

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Melbourne Data Science week is organised by:

Di Cook (Wombat – Worshop Organised by the Monash Business Analytics Team)
Phil Brierley (MeDaScIn – Melbourne Data Science Initiative)

71Days
3Hours
43Mins
51Secs