Machine Learning & Self-Driving Cars: Bootcamp with Python

Combine the power of Machine Learning, Deep Learning and Computer Vision to make a Self-Driving Car!

Interested in Machine Learning or Self-Driving Cars (i.e. Tesla)? Then this course is for you!

What you’ll learn

  • Learn how to apply Machine Learning algorithms to develop a Self-Driving Car from scratch.
  • Simulate a Self-Driving car in a realistic environment using multiple techniques (Computer Vision, Convolution Neural Networks, …).
  • Understand how Self Driving Cars work (sensors, actuators, speed control, …).
  • Learn about Computer Vision in a practical way, starting from simple examples until you are able to create an algorithm to drive a Self-Driving Car.
  • Gentle introduction to Machine Learning, all the key concepts are presented in an intuitive way.
  • Explain why Deep Learning is such a powerful ch and use it to make the car drive like a human (Behavioural Cloning).
  • Code Deep Convolutional Neural Networks with Keras (the most popular library).
  • Build, train and evaluate multiple models, from classic Machine Learning to Deep Neural Networks.
  • How to code in Python starting from the very beginning.
  • Python libraires: NumPy, Sklearn (Scikit-Learn), Keras, OpenCV, Matplotlib.

Course Content

  • Introduction –> 4 lectures • 16min.
  • Python [Optional] –> 9 lectures • 38min.
  • Python’s Essential Libraries –> 5 lectures • 29min.
  • Computer Vision –> 14 lectures • 1hr 1min.
  • Machine Learning –> 4 lectures • 20min.
  • Machine Learning Hands-On –> 11 lectures • 1hr 12min.
  • Collision Avoidance –> 8 lectures • 37min.
  • Deep Learning –> 5 lectures • 38min.
  • Deep Learning: Hands-On –> 6 lectures • 17min.
  • Control Theory –> 11 lectures • 1hr 2min.

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Requirements

  • No programming experience needed. You will learn everything you’ll need to know..

Interested in Machine Learning or Self-Driving Cars (i.e. Tesla)? Then this course is for you!

This course has been designed by a professional Data Scientist expert in Autonomous Vehicles, so that I could share my knowledge and help you understand how self-driving cars work in a simple way.

Each topic is presented at three levels:

  • Introduction: the topic will be presented, initial intuition about it
  • Hands-On: practical lectures where we will learn by doing
  • [Optional] Deep dive: going deep into the maths to fully understand the topic

What tools will we use in the course?

  • Python: probably the most versatile programming language in the world, from websites to Deep Neural Networks, all can be done in Python
  • Python libraries: matplotlib, OpenCV, numpy, scikit-learn, keras, … (those libraries make the possibilities of Python limitless)
  • Webots: a very powerful simulator, which free and open source but can provide a wide range of simulation scenarios (Self-Driving Cars, drones, quadrupeds, robotic arms, production lines, …)

Who this course is for?

  • All-levels: there is no previous knowledge required, there is a section that will teach you how to program in Python
  • Maths/logic: High-school level is enough to understand everything!

Sections:

  • [Optional] Python sections: How to program in python, and how to use essential libraries
  • Control Theory: control systems is the glue that stitches all engineering fields together
    • If you are mainly interested in ML, you can only listen to the introduction for this section, but you should know that the initial Neural Networks were heavily influenced by CT
  • Computer Vision: teaches a computer how to see, and introduces key concepts for Neural Networks
  • Machine Learning: introduction, key concepts, and road sign classification
  • Collision Avoidance: so far we have used cameras, in this section we understand how radar and lidar sensors are used for self-driving cars, use them for collision avoidance, path planning
    • Help us understand the difference between Tesla and other car manufacturers, because Tesla doesn’t use radar sensors
  • Deep learning: we will use all the concepts that we have seen before in CV, in ML and CA, neural networks introduction, Behavioural Cloning

Who am I, and why am I qualified to talk about Self-driving cars?

  • Worked in self-driving motorbikes, boats and cars
  • Some of the biggest companies in the world
  • Over 7 years experience in the industry and a master in Robotic & CV
  • Always been interested in efficient learning, and used all the techniques that I’ve learned in this course
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