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Autonomous Cars: Deep Learning and Computer Vision in Python (Udemy.com)

Learn OpenCV, Keras, object and lane detection, and traffic sign classification for self-driving cars

4.2
( 114 Reviews )

Created by: Sundog Education by Frank Kane

Produced in 2021

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What you will 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

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Quality Score

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Overall Score : 84 / 100

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Course 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:
OpenCVDeep Learning and Artificial Neural NetworksConvolutional Neural Networks Template matchingHOGfeature extractionSIFT, SURF,FAST, and ORBTensorflow and KerasLinear regression and logistic regressionDecision TreesSupport Vector MachinesNaive BayesYour 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 200,000 students around the world on Udemy alone.
Students of our popular course, "Data Science, Deep Learning, andMachine 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.
Read More product length iconTime: 13h

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Instructor Details

Sundog Education by Frank Kane

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.
Due to our volume of students we are unable to respond to private messages; please post your questions within the Q&A of your course. Thanks for understanding.

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Reviews

4.2

114 total reviews

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By Rakesh Sadhu on 10/22/2020

looks good so far

By Shannon Russell on 10/13/2020

Excellent! Clear descriptions of how cars and people see!

By Zamal Ali on 10/12/2020

I expected a better interpretation of this course but their way of teaching turned out to be ambiguous.

By Edward Larson on 9/7/2020

Yes. It was very enjoyable and rewarding.

By Andinet Negash Hunde on 9/6/2020

Awful and poor.

By Mike Buchanan on 8/21/2020

Frank provides great concise explanations of material. But the sections covered by Dr. Ryan were just okay - the demonstrations were good, but I don't think he's great at teaching.

By Satish Kumar Reddy on 8/20/2020

It is a really good course for beginners to Deep Learning and Autonomous Vehicles. Concepts are very well explained. Ryan is very descriptive but a little slow at times, but puts his point across very effectively.

By Kushagra Shrivastava on 8/19/2020

so many issues with the software no proper instructions

By Eugene Potgieter on 8/4/2020

Yes very good thanks

By Muhammad Qasim on 7/22/2020

If there is any changes it should be reflected in the lecture video as well or put some additional notes so that further inconvenience should be avoided.
For example In lecture 4.4 there is a change np.set_printoptions(threshold=np.nan) and It took 30 min for me to get back to the lecture with solution so that i will move forward in the lecture. Thus, I request to improve the current way.

By Mark Kirichenko on 7/8/2020

Rather good course covering lots of related topics.
I'd personally like to get more math/technical details to get a deeper understanding of discussed techniques.

By Ajay Ladkat on 7/7/2020

Good explanation with code and practical concepts .. !!

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Autonomous Cars: Deep Learning and Computer Vision in Python
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  • Video Duration: icon 13h
  • Price: 11.99 Track Price 11.99 Track Price
  • Provider: icon Udemy
  • Year: icon 2021
  • Language: icon English
  • Certificate: icon Yes
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