Introduction to Self-Driving Cars from Coursera

Welcome to Introduction to Self-Driving Cars, the first course in University of Toronto’s Self-Driving Cars Specialization.

This course will introduce you to the terminology, design considerations and safety assessment of self-driving cars. By the end of this course, you will be able to:

- Understand commonly used hardware used for self-driving cars

- Identify the main components of the self-driving software stack

- Program vehicle modelling and control

- Analyze the safety frameworks and current industry practices for vehicle development

For the final project in this course, you will develop control code to navigate a self-driving car around a racetrack in the CARLA simulation environment. You will construct longitudinal and lateral dynamic models for a vehicle and create controllers that regulate speed and path tracking performance using Python. You’ll test the limits of your control design and learn the challenges inherent in driving at the limit of vehicle performance.

This is an advanced course, intended for learners with a background in mechanical engineering, computer and electrical engineering, or robotics. To succeed in this course, you should have programming experience in Python 3.0, familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses), Statistics (Gaussian probability distributions), Calculus and Physics (forces, moments, inertia, Newton's Laws).

You will also need certain hardware and software specifications in order to effectively run the CARLA simulator: Windows 7 64-bit (or later) or Ubuntu 16.04 (or later), Quad-core Intel or AMD processor (2.5 GHz or faster), NVIDIA GeForce 470 GTX or AMD Radeon 6870 HD series card or higher, 8 GB RAM, and OpenGL 3 or greater (for Linux computers).

What's inside

Syllabus

Module 0: Welcome to the Self-Driving Cars Specialization!

This module will introduce you to the main concepts and layout of the specialization and discusses the major advances made in the field over the last two decades, highlighting the most recent progress made by major players in terms of safety and performance metrics, where available.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores self-driving technology, which is standard in the industry

Teaches safety frameworks, which helps learners evaluate the safety of self-driving cars

Develops programming skills in Python, which is a core skill for robotics

Taught by Jonathan Kelly and Steven Waslander, who are recognized for their work in robotics

Examines hardware and software architectures, which is highly relevant to self-driving cars

Requires programming experience, which may limit accessibility for some learners

Reviews summary

Foundation for self-driving car development

According to learners, this course provides a strong theoretical foundation and an excellent introduction to the core concepts of self-driving cars. Many praise the well-structured content and the engaging lectures. The hands-on CARLA simulator project is frequently highlighted as a valuable practical experience, allowing students to apply learned concepts. However, several students noted that the prerequisites are strictly necessary, particularly strong math and Python skills, and the CARLA simulator setup can be challenging. Overall, it's considered highly beneficial for those with the required background.

Requires solid math and programming.

"Ensure you have a strong background in linear algebra, calculus, physics, and especially Python before starting."

"The course is labeled 'Introduction' but requires significant prior knowledge to follow comfortably."

"If your math and Python skills aren't strong, you will struggle immensely."

"I found the prerequisites listed are accurate and necessary."

Lectures are clear and informative.

"The lectures were engaging and the instructors explained concepts clearly."

"I found the video lectures easy to understand and follow."

"Good explanations in the videos, which helped grasp complex ideas."

Logical flow of modules.

"The course is very well structured, building concepts module by module."

"I appreciated the logical progression of topics from theory to practical application."

"Modules are organized clearly and easy to follow."

"The course flow made sense and helped me learn effectively."

Excellent hands-on simulation project.

"The final project with the CARLA simulator was the most valuable part for me, really putting theory into practice."

"I really enjoyed the final project using CARLA to simulate a self-driving car on a racetrack. It was challenging but rewarding."

"The practical assignment in CARLA helps solidify the concepts learned in the lectures."

"Building the controller in CARLA provides great practical experience."

Provides solid theoretical grounding.

"This course provides a solid theoretical background on the fundamentals required to get into the self-driving car space."

"The theory explained is quite good and detailed for an introductory course."

"I learned a lot of theory that is essential for understanding autonomous systems."

"The content covers the fundamental concepts very well, explaining the 'why' behind things."

Simulator setup can be problematic.

"Getting the CARLA simulator environment set up correctly was the biggest hurdle for me."

"Spent a lot of time troubleshooting the CARLA installation, which was frustrating."

"The instructions for the CARLA setup could be clearer or more robust for different system configurations."

"Wish there was more support available for the simulator setup issues."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Self-Driving Cars with these activities:

Review the mathematics behind self-driving cars

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Strengthen your foundational knowledge in mathematics by reviewing concepts relevant to self-driving cars. This will improve your comprehension of the course material.

Browse courses on Linear Algebra

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Review linear algebra concepts
Refresh calculus skills
Review probability and statistics

Form study groups

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Collaborate with classmates to review course material, solve problems, and share insights. This peer-to-peer learning will enhance your understanding.

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Identify classmates with similar interests
Schedule regular study sessions
Review lecture notes and assignments together

Control engineering exercises

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Sharpen your control engineering skills by solving practice problems. These drills will strengthen your understanding of the fundamental concepts.

Browse courses on Control Theory

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Analyze system dynamics
Design controllers
Simulate control systems

Five other activities

Expand to see all activities and additional details

Show all eight activities

Tutorials on deep learning for self-driving cars

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Stay up to date with the latest advancements in deep learning for self-driving cars by following guided tutorials. This will broaden your skillset and enhance your knowledge.

Browse courses on Machine Learning

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Learn the basics of deep learning
Apply deep learning to self-driving cars
Implement deep learning algorithms

Attend industry conferences

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Connect with other professionals in the self-driving car industry to learn about the latest trends and exchange ideas.

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Research industry conferences
Register for attendance
Network with attendees

Build a self-driving car simulator

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Implement a simulator to test and refine your self-driving car algorithms. This hands-on experience will reinforce the concepts learned in the course.

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Choose a simulation platform
Design the simulator environment
Implement the physics engine
Add sensors and actuators
Test the simulator

Create a blog post about a self-driving car topic

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Solidify your understanding by synthesizing your knowledge into a blog post. This will help you articulate your thoughts and enhance your communication skills.

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Choose a specific topic
Research and gather information
Write and edit the blog post
Publish and promote the blog post

Participate in self-driving car competitions

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Test your knowledge and skills by participating in self-driving car competitions. This real-world experience will push you to solve complex problems and refine your abilities.

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Identify relevant competitions
Form a team or join an existing one
Design and develop a self-driving car
Compete in the competition

Career center

Learners who complete Introduction to Self-Driving Cars will develop knowledge and skills that may be useful to these careers:

Software Engineer

Software Engineers design, develop, and maintain software systems. They work on a variety of software applications, including operating systems, web applications, and mobile applications. This course may be useful for Software Engineers who want to work on self-driving cars, which are software-intensive systems.

See salaries and explore the career path for Software Engineer

Automotive Engineer

Automotive Engineers design, develop, and test vehicles. They work on a variety of aspects of vehicles, including engines, transmissions, and safety systems. This course may be useful for Automotive Engineers who want to work on self-driving cars, which are a new and rapidly developing area of automotive engineering.

See salaries and explore the career path for Automotive Engineer

Electrical Engineer

Electrical Engineers design, develop, and maintain electrical systems. They work on a variety of electrical systems, including power systems, control systems, and communication systems. This course may be useful for Electrical Engineers who want to work on self-driving cars, which are electrical systems that require a high level of engineering expertise.

See salaries and explore the career path for Electrical Engineer

Mechanical Engineer

Mechanical Engineers design, develop, and maintain mechanical systems. They work on a variety of mechanical systems, including engines, transmissions, and robots. This course may be useful for Mechanical Engineers who want to work on self-driving cars, which are mechanical systems that require a high level of engineering expertise.

See salaries and explore the career path for Mechanical Engineer

Control Systems Engineer

Control Systems Engineers design and implement control systems, which are used to regulate the behavior of dynamic systems. They work in a variety of industries, including automotive, aerospace, and manufacturing. This course may be useful for Control Systems Engineers who want to work on self-driving cars, which are dynamic systems that require precise control.

See salaries and explore the career path for Control Systems Engineer

Data Scientist

Data Scientists use data to solve business problems. They work with data to identify patterns, trends, and insights. This course may be useful for Data Scientists who want to work on self-driving cars, which generate a large amount of data that can be used to improve the performance of the car.

See salaries and explore the career path for Data Scientist

Quality Assurance Engineer

Quality Assurance Engineers test software and hardware products to ensure that they meet quality standards. They work with engineers and other technical experts to identify and fix defects. This course may be useful for Quality Assurance Engineers who want to work on self-driving cars, which are complex products that require a high level of quality assurance.

See salaries and explore the career path for Quality Assurance Engineer

Systems Engineer

Systems Engineers manage complex systems, using their knowledge of engineering and science to make design decisions. They work with other engineers to ensure that the system is safe, efficient, and reliable. This course may be useful for Systems Engineers who want to work on self-driving cars, which are complex systems that require a high level of engineering expertise.

See salaries and explore the career path for Systems Engineer

Product Manager

Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and marketers to ensure that the product meets the needs of the customer. This course may be useful for Product Managers who want to work on self-driving cars, which are a new and rapidly developing product.

See salaries and explore the career path for Product Manager

Project Manager

Project Managers plan and execute projects. They work with stakeholders to define the scope of the project, develop a budget, and create a timeline. They also track the progress of the project and make sure that it is completed on time and within budget. This course may be useful for Project Managers who want to work on self-driving cars, which are complex projects that require a high level of project management expertise.

See salaries and explore the career path for Project Manager

Sales Engineer

Sales Engineers work with customers to identify their needs and provide them with solutions. They work with engineers and other technical experts to develop and deliver solutions that meet the customer's needs. This course may be useful for Sales Engineers who want to work on self-driving cars, which are new and rapidly developing products.

See salaries and explore the career path for Sales Engineer

Robotics Engineer

Robotics Engineers design, build, and maintain robots, dealing with hardware and software issues. They often work in specialized fields, including aerospace, healthcare, manufacturing, and defense. This course may be useful for Robotics Engineers who want to work on self-driving cars, which is a specialized subfield of robotics.

See salaries and explore the career path for Robotics Engineer

Technical Writer

Technical Writers create documentation for technical products. They work with engineers and other technical experts to gather information and write clear and concise documentation. This course may be useful for Technical Writers who want to work on self-driving cars, which are complex products that require clear and concise documentation.

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Marketing Manager

Marketing Managers develop and execute marketing campaigns to promote products and services. They work with other marketing professionals to create and deliver marketing campaigns that reach the target audience. This course may be useful for Marketing Managers who want to work on self-driving cars, which are new and rapidly developing products.

See salaries and explore the career path for Marketing Manager

Machine Learning Engineer

Machine Learning Engineers design and build machine learning models, focusing on developing and maintaining the infrastructure and systems around the models. They work closely with data scientists to operationalize the models. This course may be useful for Machine Learning Engineers who want to build self-driving cars.

See salaries and explore the career path for Machine Learning Engineer