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Intro to Self-Driving Cars
Nanodegree Program
This introductory program is the perfect way to start your journey.
04Days07Hrs48Min51Sec
Estimated time
4 Months
At 10 hrs/week
Enroll by
August 10, 2022
Get access to classroom immediately on enrollment
Prerequisites
Programming & Mathematics
What you will learn
Intro to Self-Driving Cars
4 months to completeIn this program, you’ll sharpen your Python skills, apply C++, apply matrices and calculus in code, and touch on computer vision and machine learning. These concepts will be applied to solving self-driving car problems. At the end, you’ll be ready for our Self-Driving Car Engineer Nanodegree program!
Prerequisite knowledge
You should be comfortable reading and modifying code. You should also be comfortable with basic algebra.
Bayesian Thinking
Learn the framework that underlies a self-driving car’s understanding of itself and the world around it, and to see the world the way a self-driving car does.
Working with Matrices
This course will focus on two tools which are vital to self-driving car engineers: object oriented programming and linear algebra.
C++ Basics
This course is the first step in a rewarding journey towards C++ expertise. The goal is translation: get a program written in Python, and translate it into C++.
Performance Programming in C++
Explore how to write good code that runs correctly. We’ll focus primarily on low level features of C++, but we’ll discuss other best practices as well.
Navigating Complex Data Structures
Algorithmic thinking is a skill you’ll refine throughout your career. In this course you’ll focus on frequently used data structures and algorithms.
Visualizing Calculus and Controls
In this course you’ll learn basic calculus—the mathematics of continuity. You’ll also learn to use some of Python’s most popular visualization libraries.
Machine Learning and Computer Vision
In this course you’ll learn how a computer sees an image, and how we can use machine learning to teach a computer to identify images programmatically.
All our programs include:
Technical mentor support
Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.
Career services
You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.
Flexible learning program
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
Program offerings
Class content
- Real-world projects
- Project reviews
- Project feedback from experienced reviewers
Student services
- Technical mentor support
- Student community
Career services
- Github review
- Linkedin profile optimization
Succeed with personalized services.
We provide services customized for your needs at every step of your learning journey to ensure your success.
Get timely feedback on your projects.
- Personalized feedback
- Unlimited submissions and feedback loops
- Practical tips and industry best practices
- Additional suggested resources to improve
1,400+ project reviewers
2.7M projects reviewed
88/100 reviewer rating
1.1 hours avg project review turnaround time
Mentors available to answer your questions.
- Support for all your technical questions
- Questions answered quickly by our team of technical mentors
1,400+ technical mentors
0.85 hours median response time
Learn with the best.
Learn with the best.
Sebastian Thrun
Udacity PresidentScientist, educator, inventor, and entrepreneur, Sebastian led the self-driving car project at Google X and founded Udacity, whose mission is to democratize education by providing lifelong, on-demand learning to millions of students around the world.
Andy Brown
Curriculum LeadAndy has a bachelor's degree in physics from MIT, and taught himself to program after college (mostly with Udacity courses). He has been helping Udacity make incredible educational experiences since the early days of the company.
Cezanne Camacho
Course DeveloperCezanne is an expert in computer vision with an M.S. in Electrical Engineering from Stanford University. Inspired by anyone with the drive and imagination to learn something new, she aims to create more inclusive and effective STEM education.
Andrew Paster
InstructorAndrew has an engineering degree from Yale, and has used his data science skills to build a jewelry business from the ground up. He has additionally created courses for Udacity’s Self-Driving Car Engineer Nanodegree program.
Anthony Navarro
Product LeadAnthony is a US Army combat veteran with an M.S. in Computer Engineering from Colorado State University. Prior to being a Product Lead at Udacity, he was a Senior Software Engineer at Lockheed Martin in their Autonomous Systems R&D division.
Elecia White
Engineer, Author, HostElecia is an embedded software engineer at Logical Elegance, Inc, the author of O’Reilly’s Making Embedded Systems, and host of the Embedded.fm podcast. She enjoys sharing her enthusiasm for engineering and devices.
Tarin Ziyaee
Voyage, Director of AIAs the Director of Artificial Intelligence at Voyage Auto, Tarin works to deliver low-cost, self-driving taxis. He brings a total of 14 years experience in perception and deep neural networks working with companies such as Apple.
Intro to Self-Driving Cars Nanodegree
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Best Value
Learn
Learn the essentials of building a self-driving car, including probability, C++, machine learning, and linear algebra.
Average Time
On average, successful students take 4 months to complete this program.
Benefits include
- Real-world projects from industry experts
- Technical mentor support
- Career services
Program details
Program overview: Why should I take this program?
Why should I enroll?
Self-driving cars are the future of smart transportation, and this introductory program is the perfect way to start your journey to a self-driving car career! This program enables anyone with minimal programming experience to learn the essentials of programming a self-driving car, from machine learning to object-oriented programming to probabilistic robotics. You will learn how to solve problems in both Python and C++ as you discover what makes self-driving cars possible.What jobs will this program prepare me for?
This program does not focus on job preparation. While many of the skills you learn are foundational skills for a career in self-driving cars, the goal of the program is for you to master the core skills necessary so you can progress to the advanced curriculum. When you graduate, you can enroll in the Self-Driving Car Engineer Nanodegree program, which will fully prepare you for a career in the field. If you are new to the field of self-driving cars, you can consider this a two-stage path to career readiness.How do I know if this program is right for me?
If you're interested in self-driving cars, and already have a basic understanding of programming and algebra, then this program is right for you! If you're considering a career in this amazing field, but don't yet possess all the skills and experience necessary to start applying for jobs today, this program will be your first step toward a self-driving car career. When you graduate, you will be ready for the Self-Driving Car Engineer Nanodegree program, where you'll learn everything you need to know to launch your career.What is the difference between the Intro to Self-Driving Cars Nanodegree program and the Self-Driving Car Engineer Nanodegree program?
The Intro to Self-Driving Cars Nanodegree program is an intermediate program open to anyone with an interest in autonomous systems and some programming and/or quant background. The Self-Driving Car Engineer Nanodegree program is an advanced program focusing on in-depth knowledge of autonomous systems. The program is designed for those with moderate to high programming, technical, and/or quant skills.
Enrollment and admission
Do I need to apply? What are the admission criteria?
No. This Nanodegree program accepts all applicants regardless of experience and specific background.What are the prerequisites for enrollment?
Students should have some experience with programming—writing short scripts in a programming language—and be comfortable with algebra. You should also feel comfortable reading and modifying code that you are given, with the understanding that solving problems in code may still be challenging.If I do not meet the requirements to enroll, what should I do?
We have a number of Nanodegree programs and free courses that can help you prepare, including: Intro to Computer Science, Programming Foundations with Python, Linear Algebra Refresher, Intro to Programming Nanodegree Program.
Tuition and terms of program
How is this Nanodegree program structured?
The Intro to Self-Driving Cars Nanodegree program is comprised of content and curriculum to support eight (8) projects. We estimate that students can complete the program in four (4) months, working 10 hours per week.
Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.How long is this Nanodegree program?
Access to this Nanodegree program runs for the length of time specified above. If you do not graduate within that time period, you will continue learning with month-to-month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our Nanodegree programs.Can I switch my start date? Can I get a refund?
Please see the Udacity Program FAQs for policies on enrollment in our programs.I have graduated from the Intro to Self-Driving Cars nanodegree program but I want to keep learning. Where should I go from here?
Students who graduate from the Intro to Self-Driving Cars nanodegree program should consider the Self-Driving Car Engineer, Robotics Software Engineer, or Flying Car nanodegree programs.
Software and hardware: What do I need for this program?
What software and versions will I need in this program?
For this Nanodegree program, you will need to have the minimum equipment requirements outlined here: https://www.udacity.com/tech-requirements.Which version of TensorFlow, Keras, ROS, and C++ are taught in this program?
The following versions are taught in this program (subject to update):- TensorFlow Version 1.3
- Keras version 2
- ROS Kinetic
- Python Version 3
- C++ Version 11