Rating 4.75 out of 5 (14 ratings in Udemy)
What you'll learn- Master Machine Learning and Python
- Learn how to apply Machine Learning algorithms to develop a Self-Driving Car from scratch
- Understand why Deep Learning is such a revolution and use it to make the car drive like a human (Behavioural Cloning)
- Simulate a Self-Driving car in a realistic environment using multiple techniques (Computer Vision, Convolution Neural Networks, ...)
- Create strong added value to your business
- Gentle …
Rating 4.75 out of 5 (14 ratings in Udemy)
What you'll learn- Master Machine Learning and Python
- Learn how to apply Machine Learning algorithms to develop a Self-Driving Car from scratch
- Understand why Deep Learning is such a revolution and use it to make the car drive like a human (Behavioural Cloning)
- Simulate a Self-Driving car in a realistic environment using multiple techniques (Computer Vision, Convolution Neural Networks, ...)
- Create strong added value to your business
- Gentle introduction to Machine Learning where all the key concepts are presented in an intuitive way
- Code Deep Convolutional Neural Networks with Keras (the most popular library)
- Learn to apply Computer Vision and Deep Learning techniques to build automotive related algorithms
- Understand how Self Driving Cars work (sensors, actuators, speed control, ...)
- Learn to code in Python starting from the very beginning
- Python libraires: NumPy, Sklearn (Scikit-Learn), Keras, OpenCV, Matplotlib
DescriptionInterested 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, with the goal of sharing 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
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
Deep learning:we will use all the concepts that we have seen before in CV, in ML and CA, neural networks introduction, Behavioural Cloning
Control Theory:control systems is the glue that stitches all engineering fields together
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 in Robotic & CV
Always been interested in efficient learning, and used all the techniques that I’ve learned in this course
