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What we’re about
This is a group for anyone interested in 'Data Science'. We are not quite sure what the exact definition of a Data Scientist is, but if you deal with something generally related to converting data into useful insight then you will hopefully benefit from joining the group.
Whether you’re in business, academia, or government, and whether you’re an analyst, data miner, programmer, student, electrical engineer, computer scientist, physicist, etc, and you work with data to generate insights, build predictive models, build optimisation models, build reports/dashboards/visualisations, automate analyses, etc, using python, R, SQL, C/C+, Java, Tableau, Excel, Hadoop, etc, and you care about doing it right, efficiently, repetitively, optimally, visually, etc, then join us!
We meet every 6 weeks or so with normally 2 talks, one being of a technical nature. The evening is also for networking over beer and pizza and afterwards we normally continue the discussions down the pub.
*due to demand, we now have morning and lunchtime meetups.
The size of the group means we are reliant on our sponsors to put our events on. Please support them in return:
University of Melbourne
Bachelor of Science majoring in Data Science-https://study.unimelb.edu.au/find/courses/major/data-science/
Master of Data Science - https://study.unimelb.edu.au/find/courses/graduate/master-of-data-science/
La Trobe University - Master of Data Science
https://www.latrobe.edu.au/courses/master-of-data-science
Monash Energy Institute
https://www.monash.edu/energy-institute/home
Upcoming events (1)
See all- DuckDB for Efficient Data Science & Building High-Impact Data Science TeamsAWS Melbourne Office, Melbourne
Join us for another meetup of Data Science Melbourne where we hear from two incredible speakers.
Our first topic
DuckDB: A fast and versatile analytical database to keep in your data-science toolkitDuckDB is a fast in-process analytical database that has been generating increasing amounts of excitement amongst data engineers, data scientists, data analysts and software engineers. Its simplicity of use, combined with its blazing-fast performance, and rich feature set, make it an extremely versatile tool across a wide range of analytical applications. DuckDB is available via fully-featured Python and R clients that both have excellent integration with their respective language features and data ecosystem ecosystems.
In this talk, we’ll go on a whirlwind tour to demystify DuckDB, looking at firstly what type of data tool it is—by covering its features and comparing / contrasting it with other analytical databases. We’ll then jump into some examples of how you can leverage DuckDB for scenarios that you or your data teams might encounter as a data scientist, data analyst, or ML engineer. At the end of this talk you’ll be across what types of applications and use-cases that DuckDB could be a great fit for, and you’ll be equipped with some practical advice for how to get started exploring DuckDB and trialing it on your own projects.
Our first speaker
Ned is a lead data science engineer at Thoughtworks Australia. He’s worked across a range of sectors and domains, applying machine learning, natural language processing, and data analysis & visualization to business challenges and opportunities. Ned has used these experiences to develop strategies for making effective use of data & AI for identifying and framing the business value of data science and analytics initiatives. Alongside Simon Aubury, Ned is the author of Getting Started with DuckDB, recently published by Packt.Our second talk
Building High Performance Data Science Teams that Leverage Generative AIWe'll discuss what makes Data Science teams successful, what changes and doesn't change when we add GenAI to the mix, how to leverage organisational resources to improve outcomes, and how to manage growth.
Our second speaker
Leo has over 20 years of Advanced Analytics consulting experience across four continents and multiple industries. He currently leads the market dynamics Data Science team at SEEK. Previous careers in academia and R&D have produced three patents in Analytics and High Performance Computing and over a dozen papers in Optimisation and Machine Learning.Our Sponsor:
A big thank you to our sponsor, Method Recruitment Group, for their support and for providing us with food and drinks for this event.
Method recruits across Technology, Finance, Marketing and Not-For-Profit in Australia.
For more information on their specialised Data & Analytics division, visit: https://methodrecruitment.com.au/data-analytics/Location
Amazon Building
Level 12
555 Collins Street
Melbourne 3000When arriving in the building, please proceed to Level 1 via stairs, lifts or escalators and check-in with your photo ID. Take lift E to Level 12.
Schedule
5:30 - Networking with Pizzas & Drinks
6:00 - Ned's talk
6:30 - Q&A for Ned's talk
6:45 - Leo's talk
7:15 - Q&A for Leo's talk
7:30 - More networking
8:00 - Wrap up