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Kalman Filter Boot Camp (and State Estimation)

Master the fundamentals of Kalman filtering for state estimation in dynamic systems. Perfect for engineers and researchers.

Master the fundamentals of Kalman filtering for state estimation in dynamic systems. Perfect for engineers and researchers.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Applied Kalman Filtering Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

Instructors:

English

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Kalman Filter Boot Camp (and State Estimation)

This course includes

22 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Understand and implement Kalman filter algorithms

  • Develop state-space models for dynamic systems

  • Apply statistical concepts to state estimation

  • Implement filters using Octave/MATLAB

  • Evaluate filter performance and limitations

  • Troubleshoot common implementation issues

Skills you'll gain

Kalman Filtering
State Estimation
Control Systems
Linear Algebra
Statistical Analysis
MATLAB
Octave
Dynamic Systems
State Space Models
System Modeling

This course includes:

8.4 Hours PreRecorded video

28 assignments

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

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There are 4 modules in this course

This comprehensive course introduces students to Kalman filtering as a method for estimating hidden internal states of dynamic systems. The curriculum covers essential theoretical foundations including state-space models and stochastic systems, practical implementation in Octave/MATLAB, and performance evaluation. Students learn through a combination of theoretical concepts and hands-on programming exercises, preparing them to apply Kalman filtering techniques to real-world engineering problems.

What is the purpose of a Kalman filter?

Module 1 · 4 Hours to complete

What do I need to know about state-space models?

Module 2 · 6 Hours to complete

What do I need to know about random variables?

Module 3 · 6 Hours to complete

State-estimation application of a Kalman filter

Module 4 · 4 Hours to complete

Fee Structure

Instructor

Gregory Plett
Gregory Plett

5 rating

22 Reviews

72,282 Students

9 Courses

Leading Expert in Battery Systems and Control Engineering

Gregory Plett serves as Professor of Electrical and Computer Engineering at the University of Colorado Colorado Springs, where he has established himself as a pioneering researcher in battery management systems since 1998. His academic credentials include a B.Eng. from Carleton University and M.S.E.E. and Ph.D. degrees from Stanford University. His research focuses on advanced control systems for high-capacity batteries used in hybrid and electric vehicles, encompassing physics-based modeling, system identification, and state estimation. He has authored three influential volumes on Battery Management Systems, covering battery modeling, equivalent-circuit methods, and physics-based methods. As Director of the UCCS High-Capacity Battery Research and Test Laboratory, he leads cutting-edge research in battery pack simulation and management systems. His teaching portfolio includes advanced courses in control systems, battery dynamics, and management algorithms. A senior member of IEEE and life member of the Electrochemical Society, his work has significantly influenced the field of electric vehicle battery technology. His research innovations include developing methods for state-of-charge estimation, degradation modeling, and fast-charging protocols for battery packs.

Kalman Filter Boot Camp (and State Estimation)

This course includes

22 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.