Design and validate the telemetry system that feeds every decision
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Source path: content/lms/telemetry-systems-engineering/course.md
Track: Engineering
Difficulty: advanced
Estimated duration: 420 minutes
Coverage: 8 modules, 24 lessons
Course Overview
For engineers and data leads who need to specify, build, calibrate, and maintain the sensor-to-screen pipeline that turns raw vehicle signals into actionable insight.
Modules
- Choose the right sensor for every signal - 3 lessons - Translate engineering requirements into sensor specifications, mounting strategies, and channel budgets.
- Sample fast enough without drowning in data - 3 lessons - Master sampling theorem, anti-aliasing filters, and logger configuration so the digital record faithfully represents the analog world.
- Trust the numbers on the screen - 3 lessons - Calibrate sensors, quantify uncertainty, and build an error budget so the team knows how much faith to place in each channel.
- Build the math channels that turn raw data into insight - 3 lessons - Create derived channels—slip angle, tire load, aero balance, driver-demand indices—that compress raw signals into engineering meaning.
- Stitch laps and align traces so comparisons are fair - 3 lessons - Handle GPS drift, distance-base conversion, manual nudge, and automated alignment so overlay comparisons are precise and repeatable.
- Get data off the car and into the engineer's hands - 3 lessons - Design telemetry links, real-time dashboards, and storage architectures that balance bandwidth, latency, and reliability.
- Integrate the full pipeline and keep it running - 3 lessons - Bring sensors, logger, telemetry, and software together into a reliable system, then diagnose and repair faults under pressure.
- Look ahead to the next generation of telemetry - 3 lessons - Survey emerging sensor technologies, AI-driven analysis, and regulatory trends that will shape telemetry systems in the next decade.
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