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The University of Michigan put their entire robotics degree on GitHub.
Not one course. The whole curriculum.
ROB 101 — Computational Linear Algebra for Robotics
ROB 311 — How to Build Robots and Make Them Move
ROB 501 — Mathematics for Robotics
ROB 530 — Mobile Robotics
Every lecture video on YouTube. Every textbook on GitHub. Every problem set, every exam, every line of code.
Professor Jessy Grizzle said it best when they launched it:
"Linear algebra has become the language of computer vision, machine learning, robotics, and autonomy."
So instead of making students wait four semesters of calculus before touching a robot... they built a curriculum that starts with the math that actually matters, applied to real robotics problems from day one.
This is what open education looks like when a top-10 engineering school decides to mean it.
Free. GitHub. YouTube.
📌 [https://t.co/3STu1hzAz2]
Follow for more robotics resources!
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Weekly robotics and AI insights.
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9th @techilford Annual #TechShowcase is today! 13/6/26. Come see the past, present & the future of STEAM engagement with a family focus. See you there! https://t.co/sIxOAW8YbB
9th @techilford Annual #TechShowcase is today! 13/6/26. Come see the past, present & the future of STEAM engagement with a family focus. See you there! https://t.co/sIxOAW8YbB
Most people think AI runs on GPUs.
That's like saying the internet runs on browsers.
Modern AI is powered by an entire ecosystem of processors:
🧠 CPU → Coordinates everything
⚡ GPU → Trains massive models
🔷 TPU → Accelerates tensor operations
📱 NPU → Brings AI to phones & laptops
🚀 LPU → Delivers ultra-fast LLM responses
🌐 DPU → Handles networking, security & data movement
The interesting part?
Every AI breakthrough depends on ALL of them working together.
A trillion-parameter model is useless if:
• Data can't reach it fast enough
• Inference is too expensive
• Edge devices can't run it
• Infrastructure can't scale
The next AI race won't be won by the best model.
It'll be won by whoever builds the best compute stack.
Models get the headlines.
Chips run the world.
Which processor category do you think will see the biggest growth over the next 5 years? 👇
Machine learning Cheat Sheet
Machine learning is built step by step. Start with programming and statistics, understand core ML concepts, learn essential libraries, evaluate models properly, and apply your skills through real projects. Consistency matters more than speed.
#MachineLearning #Python #AI #DataScience #Analytics
🤖 Every robot movement starts with a joint.
From Revolute and Prismatic joints to Spherical and Planar joints, each type provides unique motion capabilities and degrees of freedom.
A quick visual guide to the fundamental joints used in robotics and industrial automation. 🚀
#Robotics #Engineering #Mechatronics #Automation #RobotArm #STEM #Technology #MechanicalEngineering
Bring #3DPrinting to your #Classroom! 🎨🖐️ @MakerBot’s free, classroom-tested guide helps students design, prototype & print their own articulated toys- no experience needed.
👉Download it here: https://t.co/owhlLnL5HC