Autonomous Cars: Deep Learning and Computer Vision in Python
What you'll learn
- Automatically detect lane markings in images
- Detect cars and pedestrians using a trained classifier and with SVM
- Classify traffic signs using Convolutional Neural Networks
- Identify other vehicles in images using template matching
- Build deep neural networks with Tensorflow and Keras
- Analyze and visualize data with Numpy, Pandas, Matplotlib, and Seaborn
- Process image data using OpenCV
- Calibrate cameras in Python, correcting for distortion
- Sharpen and blur images with convolution
- Detect edges in images with Sobel, Laplace, and Canny
- Transform images through translation, rotation, resizing, and perspective transform
- Extract image features with HOG
- Detect object corners with Harris
- Classify data with machine learning techniques including regression, decision trees, Naive Bayes, and SVM
- Classify data with artificial neural networks and deep learning
Requirements
- Windows, Mac, or Linux PC with at least 3GB free disk space.
- Some prior experience in programming.
Description
Autonomous Cars: Computer Vision and Deep Learning
The automotive industry is experiencing a paradigm shift from conventional, human-driven vehicles into self-driving, artificial intelligence-powered vehicles. Self-driving vehicles offer a safe, efficient, and cost effective solution that will dramatically redefine the future of human mobility. Self-driving cars are expected to save over half a million lives and generate enormous economic opportunities in excess of $1 trillion dollars by 2035. The automotive industry is on a billion-dollar quest to deploy the most technologically advanced vehicles on the road.
As the world advances towards a driverless future, the need for experienced engineers and researchers in this emerging new field has never been more crucial.
The purpose of this course is to provide students with knowledge of key aspects of design and development of self-driving vehicles. The course provides students with practical experience in various self-driving vehicles concepts such as machine learning and computer vision. Concepts such as lane detection, traffic sign classification, vehicle/object detection, artificial intelligence, and deep learning will be presented. The course is targeted towards students wanting to gain a fundamental understanding of self-driving vehicles control. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this self-driving car course will master driverless car technologies that are going to reshape the future of transportation.
Tools and algorithms we'll cover include:
OpenCV
Deep Learning and Artificial Neural Networks
Convolutional Neural Networks
Template matching
HOG feature extraction
SIFT, SURF, FAST, and ORB
Tensorflow and Keras
Linear regression and logistic regression
Decision Trees
Support Vector Machines
Naive Bayes
Your instructors are Dr. Ryan Ahmed with a PhD in engineering focusing on electric vehicle control systems, and Frank Kane, who spent 9 years at Amazon specializing in machine learning. Together, Frank and Dr. Ahmed have taught over 500,000 students around the world on Udemy alone.
Students of our popular course, "Data Science, Deep Learning, and Machine Learning with Python" may find some of the topics to be a review of what was covered there, seen through the lens of self-driving cars. But, most of the course focuses on topics we've never covered before, specific to computer vision techniques used in autonomous vehicles. There are plenty of new, valuable skills to be learned here!
Who this course is for:
- Software engineers interested in learning the algorithms that power self-driving cars.
Instructors
- 4.6 Instructor Rating
- 175,389 Reviews
- 1,002,542 Students
- 36 Courses
Sundog Education's mission is to make highly valuable career skills in data engineering, data science, generative AI, AWS, and machine learning accessible to everyone in the world. Our consortium of expert instructors shares our knowledge in these emerging fields with you, at prices anyone can afford.
Sundog Education is led by Frank Kane and owned by Frank's company, Sundog Software LLC. Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. As an Amazon “bar raiser,” he held veto authority over hiring decisions across the company, interviewed over 1,000 candidates, and hired and managed hundreds. He holds 26 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own company, Sundog Software, which has taught over one million students around the world about machine learning, data engineering, and managing engineers.
- 4.6 Instructor Rating
- 164,266 Reviews
- 941,288 Students
- 27 Courses
Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. As an Amazon “bar raiser,” he held veto authority over hiring decisions across the company, interviewed over 1,000 candidates, and hired and managed hundreds. He holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own company, Sundog Software, which has taught over one million students around the world about machine learning, data engineering, and managing engineers.
Due to our volume of students, I am unable to respond to private messages; please post your questions within the Q&A of your course. Thanks for understanding.
- 4.5 Instructor Rating
- 56,107 Reviews
- 444,833 Students
- 50 Courses
Hello and welcome everyone!
I’m Dr. Ryan Ahmed. I’m a professor, educator, and founder of Stemplicity School, where we make AI and data science simple, practical, and accessible for everyone. I’m passionate about creating learning experiences that are engaging, hands-on, and designed to help people thrive in a fast-changing world.
If you're just starting out in tech or aiming to sharpen your skills in AI, data science, or cloud computing, my goal is to make those complex topics feel approachable, relevant, and easy to apply. Over the past ten years, I’ve taught more than 400,000 learners across 160 countries and built a global community of over 250,000 subscribers on my YouTube channel, Prof. Ryan Ahmed, where I share tutorials and tools to help people grow their careers.
I’ve also led corporate training sessions on AI to companies like HSBC, RBC, Discover, and Barclays in US, Canada, and the UK. Earlier in my career, I held leadership roles at GM, Samsung, and Stellantis, working on electric and autonomous vehicle technologies.
I hold a MASc, PhD, and MBA from McMaster University. I’m also a licensed Professional Engineer and a Stanford-certified program manager with over 50 published research papers in AI and battery systems. But titles aside, what matters most to me is seeing others succeed.
If you're curious, motivated, and ready to learn, I’m here to help you take that next step.
- 4.5 Instructor Rating
- 25,887 Reviews
- 622,573 Students
- 54 Courses
Mitch is a Canadian filmmaker from Harrow Ontario, Canada. In 2016 he graduated from Dakota State University with a B.S, in Computer Graphics specializing in Film and Cinematic Arts.
Currently, Mitch operates as the Chairman of Red Cape Studios, Inc. where he continues his passion for filmmaking. He is also the Host of Red Cape Learning and Produces / Directs content for Red Cape Films.
He has reached over 600,000 + Students on Udemy and Produced more than 3X Best-Selling Courses.
Mitch is currently working Producing Online Educational Courses thru Red Cape Studios Inc.
Winning several awards at Dakota State University such as "1st Place BeadleMania", "Winner College 10th Anniversary Dordt Film Festival" as well as "Outstanding Artist Award College of Arts and Sciences".
Mitch has been Featured on CBC's "Windsors Shorts" Tv Show and was also the Producer/Director for TEDX Windsor, featuring speakers from across the Country.
- 4.6 Instructor Rating
- 147,941 Reviews
- 890,440 Students
- 19 Courses
Our mission is to make highly valuable skills in machine learning, big data, AI, and data science accessible at prices anyone in the world can afford. Our current online courses have reached over 500,000 students worldwide. Sundog Education CEO, Frank Kane, spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaching others about big data analysis.