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Become a Data Scientist

Gain real-world data science experience with projects designed by industry experts. Build your portfolio and advance your data science career.

Time commitment
4 months (10 hours per week) 100% online
Next start date
20 Jan 2020
Prerequisites
Python, SQL, Probability and Statistics, Machine Learning, Mathematics, Data Wrangling
A$ 2600 incl GST
Enrol now

AUSTRALIAN INDUSTRY PARTNERS


100% online, mentor supported, workplace ready

Why learn Data Science

The data science field is booming, with PwC estimating an additional 2.7 million jobs globally. Data scientists are among the most sought after positions, and yet, Australia is facing an emerging skills deficit in prepared talent for Industry 4.0. In this course, you’ll get hands-on experience running data pipelines, designing experiments, building recommendation systems, and more.

This course offers an ideal path for experienced programmers and data analysts to advance their data science careers.

How does it work

You’ll master the skills necessary to become a successful Data Scientist. You’ll work on projects designed by industry experts, and learn to run data pipelines, design experiments, build recommendation systems, and deploy solutions to the cloud. By the end of the course, you’ll have an impressive portfolio of real-world projects and valuable hands-on experience. 

Find out more in our FAQ section.

The freedom of online study

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Get RMIT certified

After completing an RMIT Future Skills course, you will earn an RMIT certificate which can be validated, recognised and shared on social media platforms.

Course Structure

Module 1

Solving data science problems

Data science processes

Building effective data visualisations

Stakeholder communication

Module 2

Software engineering for data scientists

Essential software engineering skills for data scientists

Creating unit tests

Building classes

Module 3

Data engineering for data scientists

Holistic data science process

Running pipelines and transforming data

Building models

Deploying solutions to the cloud

Module 4

Experiment design and recommendations

Designing experiments

Analysing A/B test results

Explore approaches for building recommendation systems

Module 5

Data science projects

Build your own open-ended Data Science project

Learn with Industry Experts

Get ready to meet some of the biggest names in the business

Margarita Moya
Margarita MoyaSenior analyst, Westpac

Margarita is a senior analyst with over 7 years experience across market research, analytics and financial services. As a lead Tableau developer, her current role also focuses on advocating and empowering business users to use visual analytics, building up internal Tableau education programs and the nitty gritty details of server infrastructure. Passionate about people, data and the positive social impact the two combined can achieve, she’s also a current Board Member of Engineers Without Borders Australia and is registered on Tableau Service Corps.

Kale Temple
Kale TempleCo-founder and practise director at Intellify

Kale Temple is a co-founder and practise director at Intellify where he leverages expertise in data science and machine learning to architect solutions that empower business performance and growth. He has consulted with a number of the world’s leading corporate and government organisations from over 5 years. Since 2014, he has co-founded and scaled two successful technology start-ups and as Data Scientist & Consultant at Agile BI, played a key role in building the business from the ground up into a world-leading Microsoft Power BI Partner. He holds a Bachelor of Liberal Arts and Sciences (Economics) and Masters of Economics (Economics & Econometrics) from the University of Sydney.

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