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Autonomous Cars: Deep Learning and Computer Vision in Python

Learn OpenCV, Keras, object and lane detection, and traffic sign classification for self-driving cars
4.6
4.6/5
(993 reviews)
9,244 students
Created by

9.2

Classbaze Grade®

10.0

Freshness

8.8

Popularity

8.3

Material

Learn OpenCV
Platform: Udemy
Video: 12h 45m
Language: English
Next start: On Demand

Best Computer Vision classes:

Classbaze Rating

Classbaze Grade®

9.2 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

10.0 / 10
This course was last updated on 6/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

8.8 / 10
We analyzed factors such as the rating (4.6/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

8.3 / 10
Video Score: 9.5 / 10
The course includes 12h 45m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 6 hours 08 minutes of 36 Computer Vision courses on Udemy.
Detail Score: 9.9 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

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About the course

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!

What can you learn from this course?

✓ 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

What you need to start the course?

• Windows, Mac, or Linux PC with at least 3GB free disk space.
• Some prior experience in programming.

Who is this course is made for?

• Software engineers interested in learning the algorithms that power self-driving cars.

Are there coupons or discounts for Autonomous Cars: Deep Learning and Computer Vision in Python ? What is the current price?

The course costs $14.99. And currently there is a 82% discount on the original price of the course, which was $84.99. So you save $70 if you enroll the course now.
The average price is $14.7 of 36 Computer Vision courses. So this course is 2% more expensive than the average Computer Vision course on Udemy.

Will I be refunded if I'm not satisfied with the Autonomous Cars: Deep Learning and Computer Vision in Python course?

YES, Autonomous Cars: Deep Learning and Computer Vision in Python has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Autonomous Cars: Deep Learning and Computer Vision in Python course, but there is a $70 discount from the original price ($84.99). So the current price is just $14.99.

Who will teach this course? Can I trust Sundog Education by Frank Kane?

Sundog Education by Frank Kane has created 34 courses that got 127,324 reviews which are generally positive. Sundog Education by Frank Kane has taught 606,191 students and received a 4.6 average review out of 127,324 reviews. Depending on the information available, we think that Sundog Education by Frank Kane is an instructor that you can trust.
Founder, Sundog Education. Machine Learning Pro
Sundog Education’s mission is to make highly valuable career skills in big data, data science, 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. 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.
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9.2

Classbaze Grade®

10.0

Freshness

8.8

Popularity

8.3

Material

Platform: Udemy
Video: 12h 45m
Language: English
Next start: On Demand

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