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.
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
Get Tutorial
https://www.udemy.com/course/machine-learning-self-driving-cars/157f947b776ffc56aac15cd6353bce3f3ba05bc7