Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
Coursera Introduction to Self-Driving Cars online course introduces you to the concept of self-driving cars. You will be learning the details about the hardware used in self-driving cars, components of a self-driving software stack, and how to program vehicle control and modelling. You will also analyse the current industry practices and safety structure related to vehicle development.
The Introduction to Self-Driving Cars programme by Coursera is offered in collaboration with the University of Toronto. You will learn to develop the control code that will help in navigating a self-driving car in a racetrack with the CARLA simulation environment as part of your final project. Certain hardware and software specifications are required to be able to run the CARLA simulator, which will be covered in the curriculum.
Furthermore, the Introduction to Self-Driving Cars courses houses several practice exercises, quizzes, graded assignments, and a final project. All these elements will help you learn and master the core concepts covered during the programme and reinforce your learning. Besides, upon successful completion of the course, you become eligible for the award of a course completion certificate by Coursera.
The Highlights
- Online learning
- Shareable certificate
- Offered by the University of Toronto
- Lecture videos and transcript
- Self-driving car specialisation
- Tangible career benefits
- Advanced-level of difficulty
- Self-paced training
- Free enrolment
- Financial aid
- Industry-expert mentors
Programme Offerings
- Online Course
- video transcript
- self paced training
- Shareable Certificate
- Practical exercises
- Flexible Deadlines
- pre recorded video lectures
- advanced level course
- course deliver in English
- Graded Assignments
- practice quizzes.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
Introduction to Self-Driving Cars fees details:
Particulars | Amount |
Course Fee, 1 Month | Rs. 6,634 |
Course Fee, 3 Month | Rs. 13,268 |
Course Fee, 6 Month | Rs. 19,903 |
Eligibility Criteria
The prerequisites for the Coursera Introduction to Self-Driving Cars programme include a background in electrical and computer engineering/robotics/mechanical engineering. As it is an advanced-level programme, other prerequisites such as sound knowledge of Python 3.0, linear algebra, Calculus, Physics, and statistics is necessary.
To get the certificate, students need to submit and clear the assignments. Students also need to meet the passing criteria for the programme. However, students need to purchase the course to get a certificate. Coursera will award you a shareable certificate that you can attach to your LinkedIn profile or in your CV.
What you will learn
After completing the Introduction to Self-Driving Cars online training programme, you will acquire the following knowledge:
- Hardware used for self-driving cars
- Know the major components of the self-driving software stack
- Understand the safety frameworks and on-going industry trends for vehicle development
- Be able to program vehicle control and modelling
Who it is for
Admission Details
To enrol in the Introduction to Self-Driving Cars training programme can follow the steps mentioned below:
- Get to your course on the official website of Coursera: https://www.coursera.org/.
- Look up the course by typing “Introduction to Self-Driving Cars” in the search bar.
- Choose the “Join for Free” tab on the top right corner of the page.
- Create your account on Coursera or login via Google, Facebook, or Apple. If you have registered before, just log in and enrol for the course.
Application Details
You have to log in to enrol for the Introduction to Self-Driving Cars online programme by Coursera. There is no need for filling out an application form, and you can join for free by simply signing up. Then, you get access to the course material. Besides, you can avail of the seven-day free trial for the course, if you purchase the full specialisation.
The Syllabus
Videos
- Welcome to the Self-Driving Cars Specialization!
- Welcome to the Course
- The Story of Autonomous Vehicles
- Meet the Instructor, Steven Waslander
- Meet the Instructor, Jonathan Kelly
- Meet Diana, Firmware Engineer
- Meet Winston, Software Engineer
- Meet Andy, Autonomous Systems Architect
- Meet Paul Newman, Founder, Oxbotica & Professor at the University of Oxford
- Why Should You Take This Course?
Readings
- Course Prerequisites: Knowledge, Hardware & Software
- How to Use Discussion Forums
- Glossary of Terms
- How to Use Supplementary Readings in This Course
Discussion Prompt
- Get to Know Your Classmates
Videos
- Lesson 1: Taxonomy of Driving
- Lesson 2: Requirements for Perception
- Lesson 3: Driving Decisions and Actions
- Advice for Breaking into the Self-Driving Cars Industry
Readings
- Lesson 1 Supplementary Reading: Taxonomy of Driving
- Lesson 2 Supplementary Reading: Requirements for Perception
- Lesson 3 Supplementary Reading: Driving Decisions and Actions
Assignments
- Lesson 1: Practice Quiz
- Lesson 2: Practice Quiz
- Module 1: Graded Quiz
Videos
- Lesson 1: Sensors and Computing Hardware
- Lesson 2: Hardware Configuration Design
- Lesson 3: Software Architecture
- Lesson 4: Environment Representation
- The Future of Autonomous Vehicles
Readings
- Lesson 1 Supplementary Reading: Sensors and Computing Hardware
- Lesson 2 Supplementary Reading: Hardware Configuration Design
- Lesson 3 Supplementary Reading: Software Architecture
- Lesson 4 Supplementary Reading: Environment Representation
Assignment
- Module 2: Graded Quiz
Videos
- Lesson 1: Safety Assurance for Self-Driving Vehicles
- Lesson 2: Industry Methods for Safety Assurance and Testing
- Lesson 3: Safety Frameworks for Self-Driving
- Meet Professor Krzysztof Czarnecki, Safety Assurance Expert
- Prof. Krzysztof Czarnecki on Assessing and Validating Autonomous Safety: An Impossible Task?
- Prof. Krzysztof Czarnecki's Lessons from Aerospace: Can the AV Industry Collaborate on Safety?
- Paul Newman on the Trolley Problem
- How Companies Approach Autonomous Vehicle Safety
Readings
- Lesson 1 Supplementary Reading: Safety Assurance for Self-Driving Vehicles
- Lesson 2 Supplementary Reading: Industry Methods for Safety Assurance and Testing
- Lesson 3 Supplementary Reading: Safety Frameworks for Self-Driving
- How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?
Assignments
- Module 3: Graded Quiz
Videos
- Lesson 1: Kinematic Modeling in 2D
- Lesson 2: The Kinematic Bicycle Model
- Lesson 3: Dynamic Modeling in 2D
- Lesson 4: Longitudinal Vehicle Modeling
- Lesson 5: Lateral Dynamics of Bicycle Model
- Lesson 6: Vehicle Actuation
- Lesson 7: Tire Slip and Modeling
- Challenges for the Industry
Readings
- Supplementary Readings for Module 4
- Lesson 2 Supplementary Reading: The Kinematic Bicycle Model
- Lesson 3 Supplementary Reading: Dynamic Modeling in 3D
- Lesson 4 Supplementary Reading: Longitudinal Vehicle Modeling
- Lesson 5 Supplementary Reading: Lateral Dynamics of Bicycle Model
- Lesson 6 Supplementary Reading: Vehicle Actuation
- Lesson 7 Supplementary Reading: Tire Slip and Modeling
Programming Assignments
- Kinematic Bicycle Model
- Longitudinal Vehicle Model
Ungraded Labs
- Module 4 Programming Exercise: Kinematic Bicycle Model
- Module 4 Programming Exercise: Longitudinal Vehicle Model
Videos
- Lesson 1: Proportional-Integral-Derivative (PID) Control
- Lesson 2: Longitudinal Speed Control with PID
- Lesson 3: Feedforward Speed Control
- Zoox's Approach to Self-Driving Cars
Readings
- Lesson 1 Supplementary Reading: Proportional-Integral-Derivative (PID) Control
- Lesson 2 Supplementary Reading: Longitudinal Speed Control with PID
- Lesson 3 Supplementary Reading: Feedforward Speed Control
Assignment
- Module 5 Graded Quiz
Videos
- Lesson 1: Introduction to Lateral Vehicle Control
- Lesson 2: Geometric Lateral Control - Pure Pursuit
- Lesson 3: Geometric Lateral Control - Stanley
- Lesson 4: Advanced Steering Control - MPC
Readings
- Lesson 1 Supplementary Reading: Introduction to Lateral Vehicle Control
- Lesson 2 Supplementary Reading: Geometric Lateral Control - Pure Pursuit
- Lesson 3 Supplementary Reading: Geometric Lateral Control - Stanley
- Lesson 4 Supplementary Reading: Advanced Steering Control - MPC
Assignment
- Module 6: Graded Quiz
Videos
- Lesson 1: Carla Overview - Self-Driving Car Simulation
- Lesson 2: Final Project Overview
- Final Project Solution
- Congratulations on Completing Course 1!
Readings
- Lesson 1 Supplementary Reading: Carla Overview - Self-Driving Car Simulation
- CARLA Installation Guide
Programming Assignments
- Final Project: Self-Driving Vehicle Control
Discussion Prompt
- Your Learning Journey
Instructors
University of Toronto, Toronto Frequently Asked Questions (FAQ's)
Yes, some of the modules of the Introduction to Self-Driving Cars programme have practice quizzes or graded quizzes or both. In the last module, you will be given a final project which you have to complete using the CARLA simulation.
For the Coursera Introduction to Self-Driving Cars programme, you have to use the CARLA simulator. For the same, you must have a desktop/laptop with a quad-core Intel/AMD processor (2.5 GHz or faster) with 8 GB RAM, Windows 7 or Ubuntu 16.04 or OpenGL 3, and Radeon 687- HD series/NVIDIA GeForce 470 GTX or higher.
Yes, as the Coursera Introduction to Self-Driving Cars course is an advanced-level course, all the prerequisites are necessary. You must have a background in electrical, mechanical engineering, or robotics with sound knowledge of Python 3.0 and statistics.
Yes, the Introduction to Self-Driving Cars programme by Coursera offers separate graded quizzes, assignments and programming assignments. They will be marked individually, and a final grade will be provided to you, after the completion of the programme.
Enrolling and subscribing for the Introduction to Self-Driving Cars advanced online course give you access to all the courses in the specialisation and you will be awarded an electronic certificate. It is added to your accomplishments page, from where you can either print it or link it to your LinkedIn account.