Kalman Filter Boot Camp (and State Estimation)
Taught by Gregory Plett on Coursera
- Category: Information Technology
- Level: Intermediate
- Rating: No reviews yet
- Price: $59
Included in the Coursera Plus subscription — $59/month - Duration: Four weeks of study, about 5 hours per week
- Language: English
About this course
A Coursera course taught by Gregory Plett (University of Colorado System). Introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. Develops the background theoretical topics in state-space models and stochastic systems. Presents the steps of the linear Kalman filter and shows how to implement these steps in Octave code and how to evaluate the filter’s output.
Coursera listing duration: Four weeks of study, about 5 hours per week. Level treated as Intermediate for catalogue purposes.
Imported to complete this instructor’s Coursera catalogue on CoursesAdvisors.
Pricing: Coursera enrolment, included with Coursera Plus (catalogue price US$59 / month equivalent on our site); regional plan pricing applies. Shareable certificate typically available on completion.
Who this course is for
Learners following this instructor on Coursera.
Self-paced students filling a catalogue gap.
Who it is not for
People seeking a different topic or platform.
Learners who need live 1:1 mentoring only.
What you will learn
- Core concepts from the Coursera listing.
- Practice framed by Gregory Plett.
- Self-paced modules on Coursera.
- Certificate path via Coursera Plus where offered.
Strengths
- Direct from the instructor’s Coursera catalogue.
- Fills a missing-course gap.
- Coursera Plus pricing applied consistently.
Limitations
- Editorial is compact pending deeper enrich.
- UI and tools on Coursera can change.
- Not a substitute for formal degrees unless stated.
Course FAQ
Who teaches it?
Gregory Plett.
How long is it?
Four weeks of study, about 5 hours per week.
Price?
Coursera Plus (US$59 on our catalogue).
Updated on November 5, 2026 by CoursesAdvisors Editorial Team - How we review courses
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