Udacity Self-Driving Cars Engineer Nanodegree Review: Is It Worth It?

Udacity Self-Driving Cars Engineer Nanodegree Review

A self-driving car, also referred to as driverless or autonomous car, is a vehicle that combines Artificial Intelligence, cameras, radar, and sensors to travel without a human operator. In order to fully qualify as a self-driving car, the vehicle must be able to navigate on its own without human intervention. If you are hoping to join the bandwagon and become a driverless car engineer, then you need to sign up for the Udacity Self-Driving Car Engineer Nanodegree program.

How self-driving cars work

Self-driving cars have gained quite some interest in recent years, and for a valid reason: driverless cars might just bring about the biggest societal revolution since the industrial age, and it appears like everyone is interested in it. From rumors of Apple’s self-driving cars to real-world, autonomous car applications from tech companies like Uber and Lyft, self-driving cars are poised to become a staple in the automotive industry very soon.

So what is driving so much interest in self-driving cars?

Self-driving cars have the potential to solve a lot of problems, like traffic accidents due to driver error and traffic delays. And it does not stop there: driverless cars will bring with them all sorts of new and exciting applications for a range of industries like transportation, shipping, and emergency transportation.

There is a lot to learn about self-driving cars and how they are bound to transform the future of the automotive industry, which is why Udacity has teamed up with Mercedes-Benz, NVIDIA, Uber ATG, DiDi, and McLaren to create the Self-Driving Car Engineer Nanodegree program. This online course is designed to provide an elaborate platform for individuals hoping to learn and implement skills and techniques applied by driverless car teams at the most advanced tech firms in the world. 

About Udacity

Udacity (Read review) is an online learning platform that was founded by 2 Sanford professors back in 2012 with the goal of providing industry-focused tech and businesses courses to learners from all over the world. Over the years, the academy has partnered with some of the world’s top tech companies to create over 50 Nanodegree programs getting learners geared up for the ever-growing IT and business fields.

Udacity Nanodegree programs are famous for their in-depth and comprehensive curricular. Specifically, the Udacity Self-Driving Car Engineer Nanodegree enjoys a great reputation because it has been created with the help of industry giants like McLaren, Mercedes-Benz, and Uber among others. By working with these giants, learners are set to get the chance to work with the most up-to-date technology in the market while working on Udacity’s own driverless car. This Nanodegree comes with a total of 9 real-world projects, all of which are carefully designed to cover the nooks and crannies of self-driving technologies.

What makes Udacity Self-Driving Car Engineer Nanodegree program stand out?

You are taught by industry experts

Apart from the course’s regular instructors, learners also get insights to solve real-world challenges from engineers at Mercedes-Benz, NVIDIA, and others.

A highly valuable course

With more and more companies racing to build their own self-driving cars, there is no doubt that the search for talent is on the rise. And what better talent will companies like Lyft, Otto, and Mercedes Benz get than learners who have successfully completed Udacity Self-Driving Cars Engineer Nanodegree program?

You get to work on high-value projects

At the end of this Nanodegree program, you will work with Udacity’s in-house developed self-driving car names Carla.

An opportunity to land a lucrative role

According to Udacity, previous graduates of the program have landed roles with BMW, Audi, Bosch, and Jaguar Land Rover among other automotive giants. 

Udacity Self-Driving Car Engineer Nanodegree program instructors

Sebastian Thrun

Sebastian is the Udacity president. He led the Self-Driving Car Project at Google X before co-founding Udacity.

David Silver

David leads the School of Autonomous Systems at Udacity. Before joining Udacity, he a research engineer on the autonomous vehicle team at Ford.

Ryan Keenan

Ryan has a Ph.D. in Astrophysics and has a strong passion for teaching and learning. He is also the lead instructor for the Robotics Nanodegree program.

Cezanne Camacho

Cezanne is an expert in computer vision with an M.S in Electrical Engineering from Sanford University. She is passionate about creating more inclusive and effective STEM education.

The Mercedes-Benz team

Uber Team

Udacity Self-Driving Car Engineer Nanodegree program prerequisites

Udacity recommend the following skillsets prior to enrolling for the Self-Driving Car Engineer Nanodegree.

  • Basic Linear Algebra
  • Basic Physics
  • Basic Statistics
  • Basic Calculus
  • Intermediate Python or C++

Learners are also expected to be able to communicate fluently and professionally in written and spoken English. Learners who have limited knowledge of programming, computer vision, math, or machine learning can sign up for the Introduction to Self-Driving Cars Nanodegree Program to prepare for this course.

Udacity Self-Driving Car Engineer Nanodegree course breakdown

Udacity Self-Driving Car Engineer Nanodegree is divided into 8 sections as discussed below:


In this introductory module, you will be introduced to the Innovative world of self-driving cars. You will get a glimpse of the technology that goes towards the development of driverless cars and acquaint yourself with the concepts and environments that you will be interacting with throughout the entire program.

Computer Vision

This module consists of two courses. The first course will take you through the basics of computer vision techniques to help you find lanes on the road and track other vehicles using cameras, software systems, and machine learning. You will learn how to apply vector mechanics and decision trees to extract information from videos. You will also learn how to calibrate cameras and images.

The second course will take you through advanced computer vision techniques to improve on the algorithms using distortion correction and gradient thresholding.

Project 1: Finding Lane Lines on the Road

For this project, you will need the tools you learned in the first lesson to detect lane lines in an image followed by a video. You will be writing your first code on the way to becoming a self-driving car engineer.

Project 2: In this second project, you will write complex software to detect lane lines using the car’s front camera.

Deep Learning

Deep learning is the most important concept when it comes to machine learning or autonomous systems. You will be working with Udacity Simulator, NVIDIA, and Uber ATG experts to learn how to develop and deep learning neural network using real-world data. You will learn how to code and drive a vehicle in the simulator.

Project 3: Traffic Sign Classifier

After mastering deep learning, this project will let you write codes that can identify different traffic signs

Project 4: Behavioral Cloning

In this project, you will use the deep learning knowledge you have gathered to build a deep neural network and drive a vehicle in a simulated environment.

Sensor Fusion

Identifying objects and obstacles is an important step in understanding the vehicle’s surrounding on the road. In this module, you will learn about Kalman filters, a mathematical tool used by Sensor Fusion engineers. Developed by Mercedes-Benz, Kalman filters are used to determine the approximate position of other vehicles and automobiles on the road. These filters can help you track objects that would otherwise be difficult to follow.

Project 5:

In this project, you will use C++ to apply everything you have learned Sensor Fusion and Kalman Filters.


It is never easy to determine the exact location of a vehicle using GPS due to accuracy issues As such, Localization is used to determine the car’s actual local location in the real world. This is done using Markov Localization. In this module, engineers from Mercedes-Benz will take you through the principles of Markov localization to determine the exact location of the car.

Project 6: This is a very interesting project that involves determining the precise location of the car by building a particle filter and merging it with a real map.

Path Planning

Path planning helps the self-driving vehicle move from point A to point B without causing accidents. Engineers from the Mercedes-Benz Vehicle Intelligence will take you through the 3 stages of path planning.

You will start by applying data-driven approaches to analyze the behavioral pattern of other cars on the road. Next, you will program to a self-driving car to decide the best maneuver to take. Finally, you will build a trajectory to take the decided path on maneuver.

Project 7: Highway Driving

In this project, you will use the path planner to drive your car


Actuators like brakes and steering are very crucial components of any vehicle. When it comes to autonomous cars, it is important that it is capable of triggering the right commands for steering and throttle to get the car moving. UBER ATG will take you through model predictive controllers and PID controllers. These control algorithms will teach you vital techniques for actuating the self-driving car.

System Integration

This is the final module of the Udacity Self-Driving Car Engineer Nanodegree program. This is your time to apply what you have learned in a real car. You will be introduced to Carla, Udacity’s in-house self-driving car along with the Robot Operating System that controls it. This is a team project. Along with other learners, you will make Carla move on the test track.

How long does Udacity Self-Driving Car Engineer Nanodegree program take?

Udacity estimates that you can complete this program in 6 months if you dedicate 10-15 hours per week to study. However, being a self-paced course, learners are free to set their own learning schedules. Just be sure to keep track of your project deadlines.

How much does Udacity Self-Driving Car Engineer Nanodegree cost?

Udacity has two payment options: pay per month of access, and lump sum pay. The lump sum pay for this program is $1674 while the monthly access fee is $399 for every month of course access.

Udacity Self-Driving Car Engineer Nanodegree reviews: what learners say

Udacity Self-Driving Car Engineer Nanodegree course has been reviewed by nearly 1000 graduates. Overall, the course is rated 4.8/5. Here is what learners say about this Nanodegree program:

“This Nanodegree is an excellent introduction to autonomous driving. It has a mix of classical machine learning, deep learning and robotics and every lesson is taught with a programming quiz and every module has a programming project that involves building some component of a typical self-driving car software stack. As someone with a computer science background with some robotics experience, I enjoyed every bit of this Nanodegree. I was awestruck to find out that many of the techniques taught in the Nanodegree have been used by Google self-driving car and also being used by the latest breed of autonomous vehicles from Mercedes to Baidu. I’d like to see a sequel with more advanced content from computer vision, deep learning and control perhaps centred around a state-of-the-art simulator like Carla or Apollo that includes working with LIDAR and RADAR data, programming the CAN bus, 3D segmentation, object tracking, simulation and more.” Farhan A.

“This is a one of a kind nanodegree from giving brain to the car to giving it eyes and senses , I’m learning it all ! I specifically like the part that many industry experts teach the module giving a perfect insight how real self driving car works. It’s a tough nanodegree and requires full focus but once you start the course you’ll obviously be so excited to learn new techniques. David Silver , Sebastian Thrun and the entire team at Udacity has done a commendable job. The best course I’ve ever taken and yeah , It also helped me get a job since the teaching are not only specific to SDC but also to application of Computer Vision , Deep Learning and Sensor controls. Shreyas R.

I had been an enthusiast and have been passively following the progress of deep learning and self driving cars, although i did take the advanced AI course (self driving cars) course with Udacity, it was much more theoretical. I finally had some time to take this course, i am blown away by how well thought out this course is, from course content to projects that are very practical. I can honestly say that i was enjoying the process of working through the projects as they were very practical, i feel like i have a much deeper understanding of how self driving cars work, i can navigate through this space by making sense of published papers in this space. I would also add that this is the best online class experience i had having taken several online courses. Can’t wait to start term 2. Thank you for making this process such a joy. Krishna K.

Udacity Self-Driving Car Engineer Nanodegree Review: Final thoughts

Udacity Self-Driving Car Engineer Nanodegree program is a great starting point for learners seeking to start their careers as self-driving car engineers. While this might not be the easiest subject to learn, it is definitely worth it as it is projected to be a profession of the future. Take advantage of the opportunity and leap into a new and exciting career with Udacity. There is no doubt that this is a worthwhile deal, especially with the added extras that come with the Nanodegree program.

We wish you happy learning!

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