Machine Learning & Self-Driving Cars: Bootcamp with Python

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, an expert in Autonomous Vehicles, with the goal of sharing my knowledge and helping you understand how Self-Driving Cars work in a simple way.

Each topic is presented at three levels:

• Introduction: the topic will be presented, and 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, sci-kit-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, etc.)

Sections:

• [Optional] Python sections: How to program in Python and how to use essential libraries.

• 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 and use them for collision avoidance and 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, and Behavioural Cloning.

• Control Theory: control systems are 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.

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 8 years experience in the industry and a master's in robotics & CV.

• Always been interested in efficient learning and used all the techniques that I’ve learned in this course.

Who this course is for?

• All levels, every section is separated into three levels: Introduction, Hands-On, and Deep Dive.
• Any student who wants to transition into the field of artificial intelligence.
• Entrepreneurs with an interest in working on some of the most cutting-edge technologies.
• To upgrade or get a job in the Automotive / Data Science domain.
• Any people who want to create added value to their business by using powerful Machine Learning tools.

• 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!