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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!
Why learn about self-driving cars?
To train you for big industries like autonomous vehicles, artificial industry, computer vision and IoT.
- Be industry and future ready with the latest technologies
- Learn multiple skills like AI and Computer Vision
- A disruptive industry that will open up millions of jobs
Why this course?
Learn from Industry Expert
All the learning materials and exercises have been designed with the objective of providing experience that useful in the industry
Learn by doing
While the theory is important, a hands-on approach has been proven by many studies to be the most effective and engaging way to learn
Learn anytime, anywhere
The course is hosted in Udemy, where you can view the lectures and interact with the community anytime, it even allows you to download the lectures for offline consumption
What You'll Learn
This online course enables you to make your own self-driving car with technologies used by Google, Tesla and Ford!
1.
Master Machine Learning and Python.
2.
Gentle introduction to Machine Learning where all the key concepts are presented in an intuitive way.
3.
Learn to apply Computer Vision and Deep Learning techniques to build automotive related algorithms.
4.
Simulate a Self-Driving car in a realistic environment using multiple techniques.
5.
Understand why Deep Learning is such a revolution and use it to make the car drive like a human (Behavioural Cloning).
6.
Python lectures, starting from the very beginning, learn this simple but very powerful programming language
Course Content
- How to Approach This Course – learning techniques, mindset
- Make it Engaging – Use the tools at your disposition
- Download the code of this course
- Python Installation
- Types in Python
- Structures: List & Map
- Operations (+, -, *, /)
- Functions
- Object Orient Programming (OOP)
- Classes
- Libraries / Modules
- Introduction to Python Liraries
- Numpy
- Matplotlib
- OpenCV
- Other Libraries
- Introduction to Computer Vision
- How Computer “See” Images
- Kernel & Convolution
- Image Processing with Kernels
- Thresholding
- Road Segmentation
- Why Webots?
- How to install Webots in Windows?
- How to install Webots in Linux?
- Webots too slow? (configuration)
- Webots Code :explained
- [Exercise]: Your Line Following Alrithm!
- [Advanced] How to Read a Paper?
- [Advanced] Paper: SIFT
- What’s Machine Learning?
- Train, Predict & Evaluate
- Types of Machine Learning
- ML for Self-Driving Cars
- Machine Learning Hands-On: Introduction
- Feature Engineering
- HOG
- SVM
- Performance Metrics
- Download the Dataset
- Code Explanation
- [Exercise]: Modify the code
- Useful ML Models
- Bias Vs Variance
- [Advanced] Paper: SVM
- Collision Avoidance: Introduction
- Ranging Sensors
- Cameras
- Simulation
- My Solution
- [Exercise]: Your Solution
- Path Planning
- [Advanced] RRT Code
- Deep Learning: Introduction
- How do Neural Networks Work?
- How does a Neural Network Learn?
- Convolutional Neural Networks
- Code Example
- Deep Learning Hands-On: Introduction
- Creating a Dataset
- Training
- See it drive!
- [Exercise]: Train it yourself!
- [Advanced] AlexNet
- Why Learn Control Theory
- Control Systems Map
- Stability – Introduction
- Stability – Missing in Machine Learning
- Open and Closed Loop Control
- Closed Loop Control – Cruise Control
- PID – Introduction
- PID Controller – Deep Dive
- PID Controller – How to Tune it?
- PID Controller – Why is it use SO much?
- [Advanced] Paper: PID Controller Design
Preview this course!
Take a look at
Tools used:
Industry standard tools for AI, Machine Learning and Self-Driving Cars:
Who is eligible for this course?
- Any student with basic physics and mathematics knowledge can join (all skill levels are welcome);
- Prior programming experience is NOT necessary;
- To upgrade or get a job in the Automotive / Data Science domain;
- 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;
- Any people who want to create added value to their business by using powerful Machine Learning tools.
About the author
Data Scientist & Robotics Engineer | CEO of Gradient Insight
I’ve always loved to teach, both of my parents are teachers and I’ve been teaching from a young age (it’s the family business). Given that I bought and loved many Udemy courses, I felt that it was time to try it out!
Currently I have my own company GRADIENT INSIGHT LTD where I offer Machine Learning and Artificial Intelligence Consulting services.
I truly believe that you should NEVER stop learning, if you have any comments/feedback about my course please give it to me, even if it’s not positive, it will help me to improve, and that’s what matters to me!
What our students have to say!
As an independent professional in the industry I need to keep current. I loved this course since it’s focused on the key topics around Machine Learning and AI. I highly recommend it, don’t skip the practical lectures, those provided the most value to me!
Raul Pando
CEO, Bytegrity Ltd
I was mainly interested in Self-Driving Cars when I acquired this course, I loved the Collision Avoidance and Control Theory sections, specially when using the simulator. As a data scientist I loved that the Machine Learning topics were presented in such an intuitive way.
Dr. Priyanka Singh
Senior Data Scientist, Babcock
5/5 starts – I work with a team of Software Engineers and Data Scientists, this introduced me to both worlds in simple yet powerful way. Now I understand what the team is talking about and I’m not only better at my job, but I’m more engaged!
Charles King
Systems Engineer, L3HARRIS