Get Autonomous Cars: Deep Learning and Computer Vision in Python with 90% OFF Udemy Coupon

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

4.8 out of 5
(12,768 students enrolled)
Instructor: Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team
Last Update:
Language: English

Key Takeaways — Course Overview

The following summarizes all verified data points for Autonomous Cars: Deep Learning and Computer Vision in Python, including pricing, duration, instructor, and coupon validity. All data is sourced directly from Udemy and verified by CoursesWyn on .

Course Title: Autonomous Cars: Deep Learning and Computer Vision in Python

Platform: Udemy (listed via CoursesWyn)

Instructor: Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team

Coupon Verified:

Difficulty Level: All Levels

Category: Development

Subcategory: Computer Vision

Duration: 12h 30m of on-demand video

Language: English

Access: Lifetime access to all course lectures and updates

Certificate: Official certificate of completion issued by Udemy upon finishing all course requirements

Top Learning Outcomes: Students who complete Autonomous Cars: Deep Learning and Computer Vision in Python will be able to: Automatically detect lane markings in images · Detect cars and pedestrians using a trained classifier and with SVM · Classify traffic signs using Convolutional Neural Networks

Prerequisites: Windows, Mac, or Linux PC with at least 3GB free disk space.

Price: $9.99 with coupon / Regular Udemy price: $99.99. Applying this coupon saves you $90.00 (90% OFF).

Important:

This coupon may not function properly in private/incognito browsing mode. Use a standard browser window and temporarily disable ad blockers or VPN services before clicking the redemption link to ensure the discount is applied correctly.

What You'll Learn

Completing Autonomous Cars: Deep Learning and Computer Vision in Python gives you the following verified skills and competencies in Development:

  • 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

The following background knowledge and tools are recommended before starting Autonomous Cars: Deep Learning and Computer Vision in Python. Students without these prerequisites may still enroll but should expect a steeper learning curve.

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

About This Udemy Course

The following is the full official course description for Autonomous Cars: Deep Learning and Computer Vision in Python as published on Udemy by instructor Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team. It covers the curriculum structure, teaching methodology, and topic scope for this Development 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!

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Is This Course Worth It?

Expert review by Andrew Derek, Lead Course Reviewer at CoursesWyn. Last updated: .

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Autonomous Cars: Deep Learning and Computer Vision in Python is a high-value resource for learners seeking to build skills in Development. Taught by Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team on Udemy, the 12h 30m course provides a structured progression from foundational concepts to advanced Computer Vision techniques — making it suitable for learners at all levels. The current coupon reduces the price by 90%, from $99.99 to $9.99, removing the primary financial barrier to enrollment.

What We Like (Pros)

The following advantages were identified:

  • Verified 90% price reduction makes this course accessible on any budget.
  • Aggregate student rating of 4.8 out of 5 indicates high satisfaction.
  • Includes an official Udemy completion certificate and lifetime access.

Keep in Mind (Cons)

The following limitations should be considered:

  • The depth of Computer Vision coverage may be challenging for newcomers.
  • Lifetime access is contingent on the Udemy platform's operation.
  • Hands-on projects require additional time beyond video watch time.

Andrew Derek

Lead Reviewer

View credentials →

"Given the 90% price reduction and verified 4.8-star rating, Autonomous Cars: Deep Learning and Computer Vision in Python represents one of the strongest value propositions currently available in Development. Enrollment is recommended while this coupon remains active."

Final Verdict: Worth It

Course Rating Summary

Autonomous Cars: Deep Learning and Computer Vision in Python holds an aggregate rating of 4.8 out of 5 based on 12,768 student reviews on Udemy. The distribution below shows the approximate percentage of students who gave each star rating.

4.8

12,768 Verified Ratings

5 stars
95%
4 stars
12%
3 stars
4%
2 stars
1%
1 star
1%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy. Last verified: .

Instructor Profile

The following section provides background information on Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team, the instructor responsible for creating and maintaining Autonomous Cars: Deep Learning and Computer Vision in Python on Udemy.

Autonomous Cars: Deep Learning and Computer Vision in Python is taught by Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team, a Udemy instructor specializing in Development. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.

  • Instructor Name: Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team

  • Subject Area: Development

  • Teaching Approach: Practical, project-based instruction focused on real-world application of Computer Vision skills.

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Frequently Asked Questions

The following questions and answers cover the most common queries about Autonomous Cars: Deep Learning and Computer Vision in Python, its coupon code, pricing, and enrollment process. All answers are based on verified data from Udemy as of .

Is there a verified discount coupon for Autonomous Cars: Deep Learning and Computer Vision in Python?

Yes. A verified Udemy coupon for Autonomous Cars: Deep Learning and Computer Vision in Python is available on this page, reducing the price from $99.99 to $9.99 — a saving of $90.00 (90% OFF). The coupon was last verified on March 26, 2026.

How do I apply the Autonomous Cars: Deep Learning and Computer Vision in Python coupon code?

Click the "Redeem Coupon" button on this page. The 90% discount is automatically applied to the Udemy checkout link. No manual coupon entry is needed.

How long is the Autonomous Cars: Deep Learning and Computer Vision in Python course on Udemy?

Autonomous Cars: Deep Learning and Computer Vision in Python consists of 12h 30m of on-demand video. Udemy provides lifetime access to enrolled students, allowing you to revisit all content at any time after purchase.

What skills will I gain from Autonomous Cars: Deep Learning and Computer Vision in Python?

Autonomous Cars: Deep Learning and Computer Vision in Python, taught by Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team on Udemy, covers the following competencies: Automatically detect lane markings in images; Detect cars and pedestrians using a trained classifier and with SVM; Classify traffic signs using Convolutional Neural Networks. These skills are delivered through 12h 30m of structured Computer Vision content, enabling learners to apply knowledge immediately after each module.

What is the Autonomous Cars: Deep Learning and Computer Vision in Python Udemy course?

Autonomous Cars: Deep Learning and Computer Vision in Python is a 12h 30m online course on Udemy, created and taught by Sundog Education by Frank Kane, Frank Kane, Prof. Ryan Ahmed, Mitchell Bouchard, Sundog Education Team. It covers Development topics and holds a 4.8-star rating from 12,768 enrolled students. Use the verified coupon on this page to access it at $9.99 (90% OFF the regular $99.99 price).
Andrew Derek

Andrew Derek

Expert Reviewer

Andrew Derek is a lead editor and course analyst at CoursesWyn with over 8 years of experience in online education and digital marketing. He meticulously audits every Udemy coupon and course syllabus to ensure students get the highest quality learning materials at the best possible price.

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