AI Roadmap for Electrical Engineering
A concrete path from electrical engineering into AI, built on the maths and systems you already study.
Register free See the agendaWho This Is For
Engineering Students
Anyone in an electrical or allied engineering programme who wants a concrete path into AI, not a reading list
People Unsure Where To Start
You have heard AI is important for your field but cannot see where your degree connects to it
No Coding Assumed
You do not need to have written machine learning code before. We start from what an EE degree already gives you
If you are studying electrical engineering and want AI to stop feeling like a separate world, this session is built for you.
Why AI Matters For Electrical Engineering Now
AI is not a different discipline bolted onto electrical engineering. It is already inside it, and the maths you are studying is the maths it runs on.
Across the field the same pattern keeps appearing: measurements come in faster than anyone can read them, and a model turns them into a decision. Load and solar-output forecasting and grid analytics in power and energy. Predictive maintenance on electrical machines from vibration and current signatures. TinyML running on the microcontrollers you already program. Control problems met with reinforcement learning. Signal and image processing. EV and battery analytics. None of that asks you to abandon electrical engineering; it asks you to add one layer to it.
What You'll Learn
One live session, about two and a half hours, built to leave you with a plan rather than a pile of links.
Where AI Already Fits
A quick tour of AI at work across power, electrical machines, embedded systems and control, so the rest of the session stands on real examples rather than hype.
The Map
What machine learning actually is, the skill stack underneath it, and why the EE mathematics you already have, linear algebra, signals, probability and control, is a genuine head start rather than a hurdle.
A Live Demo
One relatable electrical engineering example worked through live, end to end, so the ideas land as something you have seen run rather than something you have been told about.
The Roadmap
A phased 6 to 9 month plan with free resources at each step, and an honest account of where the EDUSHARK courses fit in and where they do not.
Projects And Careers
Projects worth building and the roles that exist at the intersection of electrical engineering and AI, so the roadmap points somewhere real.
Live Q&A
Open questions at the end. Bring the ones your syllabus has not answered.
What You Get
Register Free
A few details, no payment, no catch. We will share the joining link before the session.
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We'll share the joining link before the session. Keep an eye out for it, and feel free to bring your questions on the day.
Frequently Asked Questions
Is it really free?
Yes. The workshop is free to attend, with nothing to pay before, during or after.
Do I need prior coding experience?
No. We start from what an electrical engineering background already gives you and build up from there.
Who is this for?
Electrical and allied engineering students who want a clear route into AI. No prior machine learning or coding is assumed.
Will it be recorded?
Whether a recording is shared depends on the session. Treat it as a live event worth attending in person, and we will let registrants know either way.
How will I get the joining link?
Once you register, we will email or message you the joining link before the session. There is no automatic confirmation email, so the message you see on this page after registering is your confirmation.
After The Workshop, Go Deeper
The roadmap points at these self-paced courses, all free to read in full.
Machine Learning
Build, evaluate and deploy models, with the emphasis on measuring them honestly. Some Python assumed.
Machine Learning courseArtificial Intelligence
What AI is, how to tell whether a problem needs it, and the language, vision and ethics work that follows. No prerequisites.
Artificial Intelligence courseDeep Learning
Neural networks from tensors upward, through transformers and generative models, ending at making one cheap enough to ship.
Deep Learning courseStart your AI roadmap
A free, live, online session that turns "I should get into AI" into a plan you can actually follow. Come with questions.