Self-Driving Car Engineer Nanodegree from Udacity

Self-driving cars are set to change the way we live with technology on the cutting-edge of robotics, machine learning, computer vision, and mechanical engineering. In this program, you’ll learn the skills and techniques used by self-driving car teams at the most innovative companies in the world.

Intermediate Python (Classes, Data structures)
Intermediate C++ (Classes, Memory management, Linking)
Basic Linear Algebra (Matrices, Vectors, Matrix multiplication)
Basic Calculus (Derivatives, Integrals)
Basic Statistics (Mean, Standard deviation, Gaussian distribution)
Basic Physics (Forces)

To optimize your chances for a successful application to our Self-Driving Car Engineer Nanodegree program, we’ve created a list of prerequisites and recommendations to help prepare you for the program curriculum. Prior to applying, you should have the following knowledge:

Intermediate Python (Classes, Data structures)
Intermediate C++ (Classes, Memory management, Linking)
Basic Linear Algebra (Matrices, Vectors, Matrix multiplication)
Basic Calculus (Derivatives, Integrals)
Basic Statistics (Mean, Standard deviation, Gaussian distribution)
Basic Physics (Forces)

Certain knowledge areas are particularly important to address, and we recommended the following resources for those wishing to refine their skills in these key arenas:

Python - The free Introduction To Python Programming Course on Udacity
Probability - Khan Academy's great probability lectures
Linear Algebra - Khan Academy's great linear algebra lectures
Calculus - Khan Academy's great multivariable calculus lectures

We also recommend the following suite of Udacity courses as excellent preparation for incoming students:

For those aspiring Self-Driving Car Engineers who currently have limited backgrounds in either programming or math, we recommend the following Nanodegree programs and courses:

Programming foundations with Python (course)
Intro to Programming (Nanodegree program)
Data Analyst (Nanodegree program)

And for those who have programming and math backgrounds, but would benefit from additional studies in machine learning and/or computer vision:

Intro to Machine Learning (course)
Intro to Data Science (course)
Intro to Computer Vision (course)
Artificial Intelligence for Robotics (course)
Machine Learning Engineer (Nanodegree program)

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Learners who complete Self-Driving Car Engineer Nanodegree will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and maintaining machine learning models. They work with data scientists to collect and prepare data, and then use their expertise in machine learning algorithms to build models that can make predictions or classifications. This course can help you become a Machine Learning Engineer by providing you with a strong foundation in the fundamentals of machine learning, including supervised learning, unsupervised learning, and deep learning. You will also learn how to use popular machine learning libraries such as TensorFlow and Keras.

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Data Scientist

Data Scientists use their knowledge of statistics, machine learning, and data analysis to extract insights from data. They work with businesses to help them make better decisions by providing them with information about their customers, products, and operations. This course can help you become a Data Scientist by providing you with a strong foundation in the fundamentals of data science, including data collection, data preparation, data analysis, and data visualization. You will also learn how to use popular data science tools and technologies such as Python, R, and SQL.

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Robotics Engineer

Robotics Engineers design, build, and maintain robots. They work with mechanical engineers, electrical engineers, and computer scientists to create robots that can perform a variety of tasks, from manufacturing to healthcare. This course can help you become a Robotics Engineer by providing you with a strong foundation in the fundamentals of robotics, including robot kinematics, dynamics, and control. You will also learn how to use popular robotics simulation software such as Gazebo and ROS.

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Computer Vision Engineer

Computer Vision Engineers develop and implement algorithms that allow computers to see and interpret images. They work with computer scientists and electrical engineers to create systems that can identify objects, track movement, and understand the contents of images. This course can help you become a Computer Vision Engineer by providing you with a strong foundation in the fundamentals of computer vision, including image processing, feature extraction, and object recognition. You will also learn how to use popular computer vision libraries such as OpenCV and TensorFlow.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They work with businesses to understand their needs and then create software that meets those needs. This course can help you become a Software Engineer by providing you with a strong foundation in the fundamentals of software development, including programming languages, data structures, and algorithms. You will also learn how to use popular software development tools and technologies such as Git, GitHub, and Agile.

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Electrical Engineer

Electrical Engineers design, develop, and maintain electrical systems. They work with businesses and governments to create systems that provide power, light, and communication. This course may be useful for Electrical Engineers who want to learn more about the fundamentals of self-driving cars, including sensors, actuators, and control systems.

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Mechanical Engineer

Mechanical Engineers design, develop, and maintain mechanical systems. They work with businesses and governments to create systems that move, lift, and transform objects. This course may be useful for Mechanical Engineers who want to learn more about the fundamentals of self-driving cars, including vehicle dynamics, suspension systems, and braking systems.

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Systems Engineer

Systems Engineers design, develop, and maintain complex systems. They work with businesses and governments to create systems that meet the needs of users and stakeholders. This course may be useful for Systems Engineers who want to learn more about the fundamentals of self-driving cars, including system architecture, integration, and testing.

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Statistician

Statisticians collect, analyze, and interpret data. They work with businesses and governments to make informed decisions. This course may be useful for Statisticians who want to learn more about the fundamentals of self-driving cars, including the statistics of sensor data, traffic patterns, and accident rates.

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Physicist

Physicists study the laws of nature and matter. They work with businesses and governments to create new technologies and solve problems. This course may be useful for Physicists who want to learn more about the fundamentals of self-driving cars, including the laws of motion, energy, and momentum.

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Mathematician

Mathematicians study the properties of numbers, shapes, and patterns. They work with businesses and governments to create new technologies and solve problems. This course may be useful for Mathematicians who want to learn more about the fundamentals of self-driving cars, including the mathematics of motion, control, and optimization.

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Transportation Planner

Transportation Planners develop and implement plans for the transportation system. They work with governments and businesses to create systems that meet the needs of users and stakeholders. This course may be useful for Transportation Planners who want to learn more about the impact of self-driving cars on the transportation system, including the design of roads and highways, the planning of public transportation, and the regulation of traffic.

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Policy Analyst

Policy Analysts study and analyze public policy. They work with governments to develop and implement policies that meet the needs of citizens. This course may be useful for Policy Analysts who want to learn more about the policy implications of self-driving cars, including the regulation of self-driving cars, the liability for accidents, and the impact on public transportation.

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Economist

Economists study the production, distribution, and consumption of goods and services. They work with businesses and governments to make informed decisions about economic policy. This course may be useful for Economists who want to learn more about the economics of self-driving cars, including the impact on transportation, employment, and the environment.

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Urban Planner

Urban Planners develop and implement plans for the development of cities and towns. They work with governments and businesses to create communities that are livable, sustainable, and prosperous. This course may be useful for Urban Planners who want to learn more about the impact of self-driving cars on the built environment, including the design of streets and sidewalks, the planning of land use, and the regulation of development.

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