Optimization and State Estimation Fundamentals (Udemy.com)
Learn optimization fundamentals and state estimation techniques with this practical course!
Created by: Prof. Ryan Ahmed, PhD, MBA
Last updated June 2018
What you will learn
- Understand the theory of operation of Kalman filters and optimization strategies
- Estimate system states using Kalman Filters
- Extract parameters from data using optimization strategies
- Implement optimization and state estimation algorithms in MATLAB environment
Course Description
This course covers the details of how to develop optimization and state estimation algorithms and apply them to real world practical applications. The course covers the following topics:
- Basic of system modeling which is how to describe any mechanical or electrical system in a mathematical form.
- The theory of operation of Genetic Algorithm optimization which is extensively used in several industrial and academic applications
- How to optimize parameters using experimental data
- Implementation of Genetic algorithm logic in MATLAB environment and apply it to real world problems
- How to represent systems in State space representation form.
- Theory of operation of state estimation strategies such as Kalman Filtering
- How to apply state estimation strategies such as Kalman filtering in MATLAB to real world problems.
Instructor Details
- 4.5 Rating
252 Reviews
Prof. Ryan Ahmed, PhD, MBA
I'm Dr. Ryan Ahmed, professor, engineer, and founder of Stemplicity, where we help people get past the hype and actually build things with AI, Agentic AI, Cloud, and Data Science.
Over the past 10 years, I've taught 1 million learners across 160 countries — 700,000+ enrolled in my Udemy courses, 260,000+ subscribers on the "Prof. Ryan Ahmed" YouTube channel, and 120,000+ on Coursera. I also run corporate AI training for teams at HSBC, RBC, Discover, and Barclays across the US, Canada, and the UK. I held leadership roles at GM, Samsung, and Stellantis in Canada and the U.S., working on electric and autonomous vehicle technologies.
I hold a MASc, PhD, and MBA from McMaster University. I’m also a licensed Professional Engineer and a Stanford-certified program manager with over 60+ published research papers in AI and battery systems.
But credentials are the least interesting part. Here's what I actually believe: "AI is the biggest opportunity of our lifetime", and most people are sitting it out because they think they need to code or have a PhD. You don't. If you're willing to show up and try, I'll help you get good at this.
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Reviews
By Faiz Majeed on 10/30/2024
It is great course. But still I think he should provide code files. because one very important function in EKF implementation was not shown to us so we cannot implement same functionality by seeing the lecture. the second part, genetic algorithm for parmeters estimation was really great and I was able to implement by seeing videos. Thank you
By Satyaprakash Rout on 10/15/2023
If codes would have provided for practice then it might be awesome. The course was enjoyable but i expected MATLAB Simulink application foe GA.
By Srikar Beechu on 9/7/2022
Enjoying the session, just expecting some more information on considering co-efficients matrices, and why only first derivative of state variables. How these state variables, input variables are related . How time invariant systems are represented?
By NK Bank on 6/12/2020
The instructor is very competent at what he taught. Also I understand the topic much more than I did my own study. However, in the MATLAB part, it would be better if the sample file (m-file or code) is provided to student. So that student can do simulation at the same time. Thanks
By Walid Zorba on 3/2/2020
The instructor is very pedagogical. He explains the theoretical underpinnings of state-space modelling and Kalman algorithms quite well. But he does not devote enough time for coding. It would have been more beneficial if he solved more optimization problems to get a firmer understanding of the concepts. Examples matter.
By Hasse Lucht on 12/26/2019
Really interesting topic and very good presentation which is explained very nicely so that it - so far - can be understood without any previous knowledge of the topic
By Bishoy michael on 10/15/2019
he is perfect , he discussed important concepts with a simple way without ignore any information. thank you prof :)
By Suresh Kumar R on 8/27/2019
The course designed and content was good, I kindly request to attach the drive cycle data and matfile to the learner it will be great. Thank You Udemy Team and Professor Ryan for dedicating a wonderful course.
By Amit Dutta on 2/8/2019
I always wanted to take a course which involved the computation part for Kalman filtering. This course served to my expectation. Although I would have preferred examples that directly related to data assimilation and learning. Overall I think this was a helpful course for me.
By Shruthi Baglodi on 9/11/2018
It was a great experience to learn the SOC starting with basics.. Good job. Keep the good work going. I found it very informative and helpful. Thanks to Udemy..
Quality Score
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Overall Score : 90 / 100

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