The ultimate goal of the automotive industry is to make self-driving vehicles, and to achieve this, engineers need to be well-versed in machine learning and computer vision. This need has given rise to a comprehensive course that is specially designed to equip learners with the skills required in the emerging field of self-driving cars.
Course Description
The Autonomous Cars: Deep Learning and Computer Vision in Python course is designed to provide students with the knowledge and techniques needed to design and develop self-driving cars. The course takes a practical approach and focuses on various self-driving concepts, including object and lane detection, traffic sign classification, artificial intelligence, and deep learning.
With a course rating of 4.69768 and 1118 reviews, the Autonomous Cars: Deep Learning and Computer Vision in Python course is ranked as one of the top-rated courses, training students globally in the electric vehicle industry.
Course Content
The course covers topics such as general introduction to self-driving vehicles, road and traffic analysis, road markings, fisheye lens correction, and bird's eye view perspective. Further topics covered by the course 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
These tools and algorithms will help learners to study and be familiar with artificial intelligence, deep learning, and computer vision techniques, which are the building blocks of self-driving cars.
Instructors
This course offers learners the benefit of gaining knowledge from two renowned instructors, Dr. Ryan Ahmed and Frank Kane. Dr. Ryan Ahmed is a Ph.D. in engineering who specializes in electric vehicle control systems. He has over 20 years of experience in various industries, including aerospace and automotive, and has previously worked with General Motors, Bosch, and Fiat Chrysler Automobiles. Frank Kane, on the other hand, is a data science consultant and data scientist who has spent nine years working primarily at Amazon, where he specialized in ML. The instructors have a combined teaching experience of more than 20 years, and together they have taught over 500,000 students worldwide.
Target Audience
The Autonomous Cars: Deep Learning and Computer Vision in Python course is suitable for anyone who wishes to gain a fundamental understanding of self-driving cars control. Although it is recommended that prospective students should possess programming basic knowledge, the early course lectures extensively cover these topics, which implies that students with a basic understanding of programming language can enroll in this course.
The course is ideal for individuals who are interested in making a career in research and development of self-driving cars, electrical system designing, electric vehicle configuration, and control electronic systems.
Course Benefits
This course offers many benefits, which include:
- It provides an in-depth understanding of computer vision techniques, which are the building blocks of self-driving cars
- It helps learners to develop the skills to design and develop self-driving cars
- Students will be taught by two expert instructors with a combined teaching experience of more than 20 years
- Learners who complete the course will earn a certificate of completion
- It is a self-paced, online-based course that learners can take from anywhere in the world, at any time convenient to them.
Course Outcome
Upon completing the course, learners will have gained many valuable skills and knowledge required to design and develop self-driving cars. They will have in-depth knowledge of various computer vision techniques and how they can leverage these techniques to solve the challenges of autonomous vehicles.
Learners will also have the ability to demonstrate hands-on experience in various self-driving concepts such as traffic sign classification, lane detection, object recognition, and many more.
The Autonomous Cars: Deep Learning and Computer Vision in Python course will prepare learners to become self-driving car design and maintenance experts, positioning them at the forefront of the rapid shift from human-driven vehicles to self-driving, AI-powered vehicles. This course is highly recommended for professionals and students looking to build a career within the automotive industry.
