Udacity
Udacity Self-Driving Car Engineer Nanodegree Review — Honest Analysis
Udacity's Self-Driving Car Engineer Nanodegree was the flagship Udacity launch of 2016, built personally around Sebastian Thrun. First-cohort reviewers almost universally rated it the best MOOC they had taken. The picture in 2026 is more complicated — the curriculum still teaches a real autonomous-driving stack on real hardware (Carla, ROS), but the price now sits at $1,000-1,500 against free MIT and Stanford alternatives, and the deep-learning-heavy approach is increasingly criticised. Worth it if you specifically want the Carla capstone and your employer is paying.
Final score
from 42 analysed opinions
Published AI-researched, editor-audited
Distribution of opinions
Per-criterion scores
Reviewers praise the breadth — CV, sensor fusion, localisation, planning, control, ROS on Carla. The caveat is the curriculum is deep-learning-heavy and some flag this as the wrong architectural bet for real autonomous vehicles.
Sebastian Thrun, David Silver and the rotating industry instructors (Mercedes, BMW, NVIDIA, Uber ATG, Waymo alumni) get steady positive mentions. Reviewers who took the free CS373 first describe the nanodegree as a paid extension.
The biggest drag on the score. Original 2016-2017 price was ~$2,400; current pricing sits around $249-399/month, total ~$1,000-1,500. Flagged against free MIT 6.S094, MIT 6.832 and Stanford CS221/CS231n alternatives.
Original cohorts received mentor-graded project reviews and praised them highly, but later reviewers — including one of the most-cited HN voices — report Udacity "got rid of this feature" for self-paced learners. Slack community partially compensates.
Projects are unusually applied — behavioural cloning, lane finding, sensor fusion, path planning, and a final integration on Udacity's real Carla vehicle via ROS. The gap is that industry has moved past the deep-learning-heavy approach taught.
What learners said
What people loved
6- Real end-to-end autonomous-driving stack — perception, sensor fusion, localisation, path planning, control, ROS integration×16
- Final capstone runs your code on Udacity's actual Carla self-driving vehicle, not just a simulator×9
- Strong industry-instructor roster — Sebastian Thrun, David Silver, Mercedes, BMW, NVIDIA, Uber ATG, Waymo alumni×11
- Original cohorts praised mentor-graded project reviews as the main differentiator vs free MOOCs×8
- Active alumni and Slack community — peers who graduated still maintain connections years later×7
- Project depth — one of five first-term projects more substantial than entire competing nanodegrees×6
What frustrated learners
7- Price is the dominant complaint — originally $2,400, now $1,000-1,500 vs free MIT and Stanford alternatives×17
- Mentor feedback feature was reduced or removed for self-paced learners in later cohorts×6
- Deep-learning-heavy approach is the wrong architectural bet — industry has moved past end-to-end DL×8
- Refund and billing experiences from inactive learners have been notably poor×5
- Heavy CUDA, GPU and environment-setup overhead before you can even run projects locally×6
- Certificate carries limited weight with autonomous-vehicle hiring teams without prior robotics experience×5
- Curriculum-quality variance across the three terms — final term sensor fusion noticeably stronger than perception×4
Real quotes from real users
“I personally enjoyed most of Udacity's Self-Driving Car Engineer Nanodegree. The content was great and at the time I had a very supportive mentor (gutted they got rid of this feature).”
“I found the Udacity self-driving car program to be worth the money (and time) — even if I haven't received any financial reward yet, it's all about the journey for me.”
“Udacity's Self-driving Car Nanodegree by a wide margin — it is the best MOOC I have ever taken.”
“$2400, but was worth every penny. One of five projects in the first term is more complex than the entire ML nanodegree, and the amount of support from the peer group is extraordinary.”
“The Udacity self-driving car nanodegree trains people to build obstacle detectors and classifiers. That may be a problem, because the safer approach is flat-road detection — and the curriculum teaches the wrong architectural bet.”
“I paid for a Udacity nanodegree, had a medical problem and literally didn't log into the platform for months. Meanwhile I was getting charged thousands of dollars and when I finally emailed them about it they wouldn't refund me.”
“MOOCs are expensive. Udacity nanodegrees were $1,000. My entire Master's degree in CS was ~$1500 (in India).”
“It's super pricey as everyone has mentioned but I prefer using AWS to owning my own rig because I can download large datasets quickly. The course assumes you already have GPU access or are willing to pay for it on top of tuition.”
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How we evaluated this
This review synthesizes 42 opinions collected across the public web. Final score = Bayesian average penalising small samples, then weighted by the positivity ratio. No paid placements, no hidden agenda.
- 34 from Hacker News
- 8 from Blogs