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Intro to Self-Driving Cars

This innovative curriculum in Australia is teaching you all the fundamentals to get you started in autonomous vehicles.


    4 months
    (10 hours per week)
    4 February 2019
    (Limited places available)
    • 6 May 2019
    A$2,598 GST inc.
    Learn about payment options here
    Basic experience in programming and algebra. Comfortable reading and modifying code


  • nvidia
  • bosch
  • holden
  • kapsch
  • ITS
  • Mtaiq


Why learn Intro to Self-Driving Cars?

By 2020 the autonomous vehicle market will be worth AU$120 billion (Accenture) - we cannot ignore the role that autonomous vehicles will play both here in Australia and on a global stage. This is Australia’s first dedicated online short course committed to educating the next wave of future engineers. This course will teach you the fundamentals of building a self-driving car with only minimal programming experience. You will learn both Python and C++ , providing you with an exhilarating first step into this exciting world.

How it works

This course will introduce you to all the tools vital for self-driving car engineers. You will learn how a computer sees an image and how to use machines to teach a computer to identify images programmatically. During the 4 months, you’ll get to practise how to write code for self-driving cars, and plan and visualise the trajectory for it. You will have access to Udacity's cutting-edge learning platform, combined with localised support from industry experts and be welcomed into a community of peers and leading local employers.  Your experience will be assessed and credentialed by a world-leading university.

Skills you learn

Bayesian Thinking, C++, algorithmic thinking, object-oriented programming, linear algebra, Python's visualisation libraries for trajectory planning, machine learning and computer vision.

Find out more in our FAQ section.

  • Connecting you with industry

    Connect with local industry experts including Kapsch, Holden, Mtaiq and ITS through weekly tutorials and webinars, who are all looking for the next wave of talent to address the skills shortage in these critical areas.

  • Career ready, real world skills

    RMIT has partnered with Udacity to multiply the power of a world-leading university with the best of Silicon Valley, topped off with industry mentors from Australia's vibrant local ecosystem.

  • Expert industry mentors

    On top of the live classes that will allow you to learn alongside your peers, we recognise the power of working with a mentor who has been there and done that. You will have scheduled 1:1 mentoring sessions at set milestones in your course. This is a chance to take stock and get further personalised support in your learning and career journey.

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  • RMIT credentials

    The cutting-edge skills you learn will be rigorously assessed and recognised by both a leading University and employers in the field. You will also be eligible for credits into selected degree programs at RMIT University.

  • Convenient and flexible learning

    The beauty of online learning, is you can fit it in and around your work and personal schedule. RMIT experience provides structure on top of this, including support from our Course Managers and Student Success Team, interaction with peers and industry experts via a virtual classroom and weekly check ins with your mentor.

  • Collaborative online experience

    We know our students are most successful when we combine the great advantages of flexibility with the amazing interactions that happen between peers, experts and industry employers. Join the slack channels to interact with your classmates here in Australia and get feedback from the global Udacity community.

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Course outline

Module 1

Bayesian Thinking

Learn the framework that underlies a self-driving car's understanding of itself with basic algebra.


Joy Ride

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Module 2

Working with Matrices

Focus on two tools which are vital to self-driving car engineers: object oriented programming and linear algebra.


Implement a matrix class

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Module 3

C ++ Basics

First step towards C++ expertise. The goal is translation: get a program written in Python and translate into C++


Translate Python to C++

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Module 4

Performance Programming in C++

Explore how to write good code that runs correctly. Low level features of C++ and other best practices.


Performant C++

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Module 5

Navigating Complex Data Structures

Algorithmic thinking and frequently used data structures.


Planning an optimal path

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Module 6

Visualising Calculus and Controls

Basic calculus – the mathematics of continuity. Python's most popular visualisation libraries.


Trajectory visualiser

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Module 7

Machine learning and Computer Vision

Learn how a computer sees an image and how to use machine learning to teach a computer to identify images programmatically.


Image classifier from scratch

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Learn with industry experts

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

Kate Cousins

Kate Cousins

Lead Technical Specialist Engineer – Active Safety Lead, Holden

After completing my Bachelor of Engineering in Robotics and Mechatronics, I joined Holden as a member of the Engineering Graduate Program. Now, over 12 years later I am the Lead Technical Specialist Engineer for Active Safety and Automated Driving.  GM is one of the leaders in the automated driving space, so being involved in this area is amazingly rewarding and exciting. I am involved in ensuring that these features are appropriate for Australian conditions as well being involved on global products. The work I do directly impacts GM’s vision of “zero crashes, zero emissions, zero congestion”. My job is amazing, but it is the culture and people at Holden that makes me enjoy coming to work every day. I am proud to say I work at Holden.

Nathan Nguyen

Nathan Nguyen

Community Manager, MTAiQ

Nathan is the Community Manager for MTAiQ, Australia’s first automotive innovation hub, which has been established by the Motor Trades Association of Queensland. A resourceful innovator and entrepreneur, Nathan has over 10 years of experience working in the automotive industry. With a background in economics, business and marketing, Nathan has been involved in developing and launching several start-up businesses and engaging with, and providing solutions to, the MTAiQ community and assisting clients.

Rodrigo Perez Klenner

Rodrigo Perez Klenner

Solution Consultant, Kapsch

Rodrigo is highly skilled Electrical Engineer with a Master of Arts in Statistics and a strong technical knowledge gained through more than 10 years of professional experience gathering, analysing business requirements and delivering solutions while acting as the nexus between the stakeholders and the technical team. Rodrigo has participated in projects with different complexities as Architect, Team Leader, System Engineer during the design phase defining user histories, uses cases and supervising the delivery and testing phases of the project. He has a passion for innovation and understanding the mechanics of how things work.

Kelvin Lwin

Kelvin Lwin

Knowledge Architect | Senior Deep Learning Instructor, Nvidia

After spending nearly a decade at UC Berkeley, Kelvin decided to repay his debt to the public education system by helping build UC Merced. He spent seven years teaching 4,500 students across 55 classes, while redesigning the undergraduate Computer Science curriculum. He is now busy designing curricula at NVIDIA’s Deep Learning Institute (DLI) to democratize access to the latest technologies across many disciplines, industries and geographies. Kelvin helped DLI reach over 100K developers worldwide directly and in collaboration with Udacity and Coursera/ He continues to search for ways to leverage AI to solve the Paradox of Progress.

Xavier Vagedes

Xavier Vagedes

Project Leader Automated Driving, Bosch

Xavier is a Systems Engineer with over 15 years’ experience in the development of vehicle safety technologies. His first contact with Automated Driving was in 2002, working on a driverless truck project at Daimler-Benz Research in Germany. Since working at Bosch, he has moved around the world working on the development of Chassis Control and Advanced Driver Assistance Systems. As Scrum Master, and then Project Leader for Automated Driving, he has been focusing on the challenges of system integration of complex networked vehicle systems since the start of the Bosch Automated Driving program.



Intro to Self-Driving Cars (1 course)

Enrol in the Intro to Self-Driving Cars short online course, designed by industry experts. Course runs for 4 months.

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Start date: 4 February 2019

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You will be eligible for a certificate on completing this course.

We estimate that you will need a total of 50 hours to complete this course over 8 weeks.

1) A computer with good internet access
2) Slack (web or free on the App Store)
3) ZOOM Cloud Meetings (web or free on the App Store)

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