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AI-Assisted RTOS Engineering - Printable Version

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AI-Assisted RTOS Engineering - Courses2025 - 01-26-2026

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Free Download AI-Assisted RTOS Engineering
Published 1/2026
Created by BHM Engineering Academy
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 92 Lectures ( 9h 6m ) | Size: 7.33 GB

A professional real-time workflow with task contracts, measurable proofs, and ship-ready packaging.
What you'll learn
✓ Design deterministic RTOS task architectures with AI Assistance and task contracts
✓ Enforce real-time deadlines, priorities, and ISR rules with AI Assistance
✓ Measure latency, jitter, and queue health using proof harnesses with AI Assistance
✓ Control and validate RTOS code changes using patch-based workflows with AI Assistance
✓ Diagnose and fix real RTOS failures under load with AI Assistance and evidence
Requirements
● NUCLEO-F411
Description
This course contains the use of artificial intelligence.
Imagine you have been assigned to deliver the firmware for a real device, not a demo.
A small industrial edge unit is going into pilot deployments soon. It must
• sample data on a fixed schedule
• process it reliably under load
• publish telemetry on time
• respond to asynchronous events instantly
• survive faults and recover safely
Now the constraint
Your team is using AI assistance to move faster, but you are not allowed to ship "RTOS spaghetti".
Your lead says
• "Every task needs a contract, a rate, a priority rationale, and a timeout policy."
• "Interrupts must be wired correctly, with proper RTOS priority rules."
• "Proof must be measurable, repeatable, and captured as evidence."
• "No blob code. No rewrites. Patch-based changes only."
That is exactly what this program trains you to do.
This is not a FreeRTOS feature tour
What you build
You build a cohesive real-time device firmware project that forces the full set of RTOS skills naturally.
The project is an industrial edge system (FieldMonitor-RT style) that includes
• a periodic sampling pipeline with deadlines
• event-driven processing triggered by real event
• telemetry that does not starve time-critical work
• asynchronous inputs via ISR to task notifications
• mode control, diagnostics, and safe behavior under fault conditions
Why this matters now
Real-time firmware is becoming more complex, and AI is becoming a permanent part of how teams build.
The engineers who stand out will not be the ones who can generate code.
They will be the ones who can
• control AI output
• enforce contracts and bounded behavior
• prove timing and correctness
• ship with evidence
That is what AI-Assisted RTOS Engineering gives you.
What you get when you add this now
-A complete RTOS build that turns your driver foundation into a real product system
-Structured AI instruction packs that enforce patch discipline and contract-first thinking
-A target proof harness that measures latency, deadlines, and queue health
-A failure library of real RTOS issues and fixes (priority inversion, starvation, ISR misuse, queue overflow)
-Release-ready packaging habits: docs, diagnostics, and evidence artifacts
Enroll now and learn the professional workflow for building deterministic FreeRTOS systems with AI assistance, proof, and release discipline.
Who this course is for
■ Embedded engineers who already use FreeRTOS and want to ship deterministic systems with AI Assistance, not demos or spaghetti code
■ Firmware professionals responsible for real devices who must justify task design, priorities, ISR behavior, and timing with evidence
■ Senior or mid-level engineers adopting AI Assistance who need disciplined, contract-driven RTOS workflows suitable for production
Homepage
Code:
https://www.udemy.com/course/ai-assisted-rtos-engineering/

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