START WITH ROS: Build Real Robotics Applications on the edge by Jeremy Cohen

START WITH ROS: Build Real Robotics Applications on the edge

Discover how real self-driving cars work, build embedded Computer Vision projects, and break the barrier between online courses and reality.

πŸš€ After Launch - Price goes up 10€ every 24 hours until it reaches 199€
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What's included?

βœ”οΈ Build Robotics Applications on the edge
βœ”οΈ The ROS Cheatsheet
βœ”οΈ Embedded Computer Vision Guide and Raspberry Pi 4 Tutorials
βœ”οΈ Real-world portfolio projects
βœ”οΈOne-on-one onboarding sessions (optional)
βœ”οΈ VIP Contact and Support

How do real robots work?

What is it like in a real self-driving car company? 
Do people have specific algorithms and programs? Can you learn these?

Can you relate?
  • You learned to detect obstacles based on an image, but you never learned anything about how to work with the camera, how to integrate the camera in a real robot, or even how to calibrate it... 
  • You've learned about obstacle detection, but all you ever did was a Jupyter Notebook project...
  • You've learned about Kalman Filters, but your project seems off reality...
  • You know how LiDARs work, but you would never plug a LiDAR to a computer and process point clouds...

    In other words, you have the algorithm skills, but not the integration skills.

πŸ‘‰ Robotic OS allows you to program real robots, and if you don't know it, you're burning 50% of your chances not learning ROS.

You may know Machine Learning, Deep Learning, Computer Vision, Robotics, C++,... But something is still missing!

Hard vs Smart

In this course, we'll focus on the project. Nothing else matters. Building a project that works with ROS.

  • The course is 100% practical.
  • It's not theoretical.
  • Third, this course will require you at some moments to install things, compile, try, fail, and retry. If you're expecting to copy and paste solutions, to click buttons, you're not at the right place.
This course is what I wish I had when I started.

Introducing START WITH ROS: Build Real Robotics Applications on the edge

Learn the key ROS concepts, familiarize yourself with real hardware, and build real life Computer Vision projects.

Master the Fundamentals

Learn how to use ROS, master the 5 Pillars and the fundamentals to get started easily. Work with real self-driving car data all along and create a fantastic project.

Concepts: ROS Noetic, Catkin Packages, Nodes, Topics, Messages, Publishers, Subscribers, Services, Actions, Rosbags, command lines...

Learn Embedded Computer Vision with ROS

ROS is the heart of a self-driving car. You won't simply learn ROS, but you'll build a ROS Project that will subscribe to the camera image, and publish the bounding boxes it founds in real time!

Concepts: Embedded Programming, OpenCV, YOLOv4, TensorFlow, TFLite, CV Bridge, Architectures.

Work with Real Hardware

The course is built using a Raspberry Pi. While you can follow the course on your own computer, you have the option to get a Raspberry Pi and set the first stone in your future Do It Yourself project.

Concepts: ARM Architectures, Desktop vs Embedded OS, Using a Raspberry Pi, RAM and processing, Embedded Computer Vision...

What you'll learn

βœ”οΈ How do real self-driving cars work? What are the ROS Fundamentals you should know?

βœ”οΈ 80/20 - What are the 20% concepts you can master to build 80% of the projects?


βœ”οΈ ROSBAGS - Read and Record real self-driving car data

βœ”οΈ Build your first ROS Application using pre-recorded data from a real autonomous car

βœ”οΈ (PDF) YOUR ROS CHEATSHEET TO GET STARTED FASTER AND MASTER THE MOST IMPORTANT CONCEPTS

βœ”οΈ How to use YOLOv4 for obstacle detection with ROS using TensorFlow, OpenCV, and TFLite

βœ”οΈ IMAGE PROCESSING - Learn to avoid the main problems engineers face when using ROS with OpenCV

βœ”οΈ CUSTOM MESSAGES - How to implement the 4 Pillars of self-driving cars?

βœ”οΈ ROS Compilation - How to write a CMAKE and a Package file to build ANY ROS PROJECT in Python or C++.

βœ”οΈ BUILD YOUR FIRST ROS PROJECT WITH REAL SELF-DRIVING CAR DATA.

βœ”οΈ (Optional) Get full guidance to work on a Raspberry Pi. Pre-installed images, practical warnings, and more...

βœ”οΈ 3 MAIN PLATFORMS to run code on embedded hardware: Where is the future of self-driving cars going?

βœ”οΈ RASPBERRY PI: The Full Experience from Unboxing to building a real robot

βœ”οΈ How to plug a real camera, make it work, and receive image data with ROS? Analyze a real camera code.

βœ”οΈ BUILD THE FOUNDATIONS OF YOUR FUTURE DO IT YOURSELF AUTONOMOUS CAR

FAQs

What are the prerequisites to follow the course?

The course is open to beginners.
However, there are a few prerequisites:

  • Be familiar with Linux Command Lines (cd, ls, cp, ...)
  • Be able to code in either Python or C++.

Do I have to buy a Raspberry Pi?

No. The course is entirely doable in your own computer using an Ubuntu Virtual Machine (8Gb RAM recommended) or using your computer if you already have Ubuntu pre-installed.

I do recommend using a Raspberry Pi if you want to get the full experience of embedded programming and get closer to coding real robots.

Whatever you chose, everything is guided and you will have pre-installed images and os.

How long is the course?

It's estimated between 6 and 12 hours depending on your abilities to decide on an installation and solve the projects.

What will I be able to do after this course?

After this course, you will be able to use ROS for Computer Vision projects.

It means that you will know how to understand real self-driving car codes and architectures, that you will have coded a system that publishes obstacle information, and that you will be able to run this on your laptop or an embedded computer.

One of the two most important requirements in a self-driving car engineer position is to master ROS. The other is C++.

ROS is the key element of self-driving cars. Without ROS Knowledge, you're removing 50% of the companies you could potentially apply to. Master ROS Today, and fill the gap between your learning and the reality.

Enroll Now

Jeremy Cohen

Artificial Intelligence & Self-Driving Car Engineer, Head Dean of France School of AI, and Machine Learning Lecturer.
I started thinkautonomous.ai to help aspiring AI & Self-Driving Car Engineers to land their dream job. Working in the industry of the future requires skills and passion. You can build your skills here, where you'll create relevant projects that are used every day in autonomous robots & AI engines.

πŸ‘‰ Learn more