AI Director · Automotive
AI for Automotive: A Playbook for AI Directors
You already know AI matters for your roadmap. What you need now is how it plays out in automotive: where computer vision fits on the production line, what the UNECE R155 cybersecurity rule means for your OTA strategy, how Tesla, BYD and the German OEMs are actually deploying AI in design and manufacturing versus what gets announced in press releases. This track gives you that grounding alongside the general AI curriculum, so you're not learning theory in one place and translating it to your sector in another.
You'll work through interactive tools built around real automotive scenarios, a playbook for sequencing AI initiatives across R&D, production and aftersales, and a sector-specific assessment that tells you exactly where your knowledge holds up and where it doesn't. This is built for someone who has to make the call on AI investment and defend it to a board that wants numbers, not buzzwords.
31 lessons · ~6 h · resumes where you left off
Your program
A focused program built on your vertical's content: the sector first, then your discipline applied to it.
The generalist AI track
The full craft of the discipline, beyond your sector.
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Frequently asked questions
Who is the AI for Automotive track designed for?
It targets AI Directors and equivalent decision-makers in automotive who have to approve AI investment and justify it to a board. The material assumes you already accept that AI matters and skips the persuasion stage to focus on how it applies to OEMs, suppliers, ADAS, manufacturing and regulation.
What is the difference between this track and a general AI curriculum?
The general AI curriculum covers the fundamentals; the automotive track adds the sector layer on top of it, so you get both in one place. Instead of learning theory in one course and translating it to your industry afterwards, you see computer vision applied to a production line and cybersecurity rules applied to an OTA strategy.
What does the track actually contain besides lessons?
Three things complement the lessons: interactive tools built around real automotive scenarios, a playbook for sequencing AI initiatives across R&D, production and aftersales, and a sector-specific assessment. The assessment is there to show you where your knowledge holds up and where it doesn't before you commit budget.
Is there a certification or diploma at the end?
No. There is no diploma, no state-recognised certification and no affiliation with a school or university. Reading is free and open; an account only saves your progress through the lessons and your assessment results.
Why does UNECE R155 come up in an AI track?
Because R155 sets cybersecurity management requirements for vehicles, and it constrains how you deploy over-the-air updates, which is the delivery channel for most AI features shipped after production. The track covers what the rule means in practice for an OTA strategy rather than treating regulation as a separate compliance topic.
Does the track look at what specific carmakers are doing with AI?
Yes, and with a deliberate filter: it separates what Tesla, BYD and the German OEMs actually deploy in design and manufacturing from what appears in press releases. That gap matters when you benchmark your own roadmap, because announced capability and installed capability are rarely the same thing.