The Complete Self-Driving Car Course - Applied Deep Learning
What you'll learn
- Learn to apply Computer Vision and Deep Learning techniques to build automotive-related algorithms
- Understand, build and train Convolutional Neural Networks with Keras
- Simulate a fully functional Self-Driving Car with Convolutional Neural Networks and Computer Vision
- Train a Deep Learning Model that can identify between 43 different Traffic Signs
- Learn to use essential Computer Vision techniques to identify lane lines on a road
- Learn to build and train powerful Neural Networks with Keras
- Understand Neural Networks at the most fundamental perceptron-based level
- A working computer
- No experience required!
Self-driving cars have rapidly become one of the most transformative technologies to emerge. Fuelled by Deep Learning algorithms, they are continuously driving our society forward and creating new opportunities in the mobility sector.
Deep Learning jobs command some of the highest salaries in the development world. This is the first, and only course which makes practical use of Deep Learning, and applies it to building a self-driving car, one of the most disruptive technologies in the world today.
Learn & Master Deep Learning in this fun and exciting course with top instructor Rayan Slim. With over 28000 students, Rayan is a highly rated and experienced instructor who has followed a "learn by doing" style to create this amazing course.
You'll go from beginner to Deep Learning expert and your instructor will complete each task with you step by step on screen.
By the end of the course, you will have built a fully functional self-driving car fuelled entirely by Deep Learning. This powerful simulation will impress even the most senior developers and ensure you have hands on skills in neural networks that you can bring to any project or company.
This course will show you how to:
Use Computer Vision techniques via OpenCV to identify lane lines for a self-driving car.
Learn to train a Perceptron-based Neural Network to classify between binary classes.
Learn to train Convolutional Neural Networks to identify between various traffic signs.
Train Deep Neural Networks to fit complex datasets.
Master Keras, a power Neural Network library written in Python.
Build and train a fully functional self driving car to drive on its own!
No experience required. This course is designed to take students with no programming/mathematics experience to accomplished Deep Learning developers.
This course also comes with all the source code and friendly support in the Q&A area.
Who this course is for:
- Anyone with an interest in Deep Learning and Self Driving Cars
- Anyone (no matter the skill level) who wants to transition into the field of Artificial Intelligence
- Entrepreneurs with an interest in working on some of the most cutting edge technologies
- All skill levels are welcome!
Rayan is a full-stack software developer based in Ottawa, Canada.
Rayan has been appointed as an acting tech lead at Canada's IRCC. His main role is to set up infrastructure monitoring tools to extract health metrics from cloud-native applications.
Rayan also takes leadership roles as he guides other developers towards building Spring Boot applications that implement Enterprise Integration Patterns using the Apache Camel framework. His supervision extends to showing developers how to deploy their applications on the Red Hat Openshift platform using the Kubernetes package manager Helm.
Outside of his daily work, Rayan loves to explore new technologies. He is deeply passionate about Artificial Intelligence and Data Visualization.
In Rayan's free time, he loves to teach!
Hi I'm Amer. I'm a full-time developer with a specialized interest in Artificial intelligence (AI). AI is now taking on more sophisticated roles that can truly amplify human capabilities.
With a background in Mechanical Engineering and computer science I have always looked for ways to use the power of AI to create practical solutions that revolutionize the way we live.
I aim to make artificial intelligence more accessible to all students, no matter the skill level!
Jad studied mechanical engineering at the University of Ottawa. Jad also has extensive experience in software development, cloud development, machine learning, computer vision, mathematical modeling, computer simulation, and intelligent systems. Jad has also developed many deep learning applications, and is currently pursuing an interest in autonomous machines and Full Stack Development.
Hi! I'm Sarmad, and I have graduate level expertise in Mechanical Engineering. My main areas of interest and research include autonomous robotics, self driving car technology and machine learning.
In my spare time, I enjoy teaching courses on Udemy and sharing my knowledge with all of you!