Parameter Estimation Courses and Certifications

UofU Data Science

Linear Regression and Parameter Estimation in R - Lecture 17

Master linear regression techniques in R while exploring parameter estimation and random variable estimators through hands-on statistical analysis and practical applications.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

UofU Data Science

Hidden Markov Models - Parameter Estimation and Efficient Inference

Master parameter estimation and efficient inference techniques for Hidden Markov Models, exploring key algorithms and mathematical foundations for probabilistic sequence modeling and pattern recognition.

• YouTube
• 1 hour
• Self-Paced
• Free Video

UofU Data Science

Hidden Markov Models: Parameter Estimation, Inference, and Viterbi Algorithm

Master parameter estimation and inference in Hidden Markov Models (HMM), including Viterbi algorithm implementation for sequence analysis and probabilistic modeling.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

JuliaHub

Model Calibration and Parameter Estimation with JuliaSim Model Optimizer

Master parameter estimation and model calibration techniques using JuliaSim Model Optimizer to match data with models through automated optimization, inverse problem solving, and model autocomplete features.

• YouTube
• 51 minutes
• Self-Paced
• Free Video

JuliaHub

Control of Rotary Pendulum - Parameter Estimation Using Maximum-Likelihood - Part 5

Dive into maximum-likelihood estimation for rotary pendulum control using unscented Kalman filters and gradient-based optimization with automatic differentiation in Julia.

• YouTube
• 15 minutes
• Self-Paced
• Free Video

The Julia Programming Language

ParameterEstimation.jl - Algebraic Parameter Estimation in ODEs

Discover algebraic parameter estimation in ODEs using ParameterEstimation.jl, replacing optimization with algebraic systems and Gaussian Process Regression for noise robustness.

• YouTube
• 10 minutes
• Self-Paced
• Free Video

Estimate Geometry Using Homographies and RANSAC with Python

Turn feature matches into geometry: estimate homographies with RANSAC in Python, visualize inliers versus outliers, warp images into alignment, and sweep ratio and threshold values.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Probabilistic Graphical Models 3: Learning

305 ratings at Coursera

Learn how graphical models are learned from data: maximum likelihood and Bayesian parameter estimation, undirected model training, Bayesian network structure search, and EM for incomplete data.

• Coursera
• 8 weeks, 8 hours a week
• Self-Paced
• Paid Course

Career Certificate

Applied Kalman Filtering

39 ratings at Coursera

Derive, design, and implement linear, nonlinear, and particle Kalman filters in Octave, debugging anomalous behavior across state estimation, target tracking, parameter estimation, and navigation.

• Coursera
• 16 weeks, 5 hours a week
• Self-Paced
• Paid Course
• 4 courses

Probability and Statistics III: A Gentle Introduction to Statistics

This course provides an introduction to basic statistical concepts. We begin by walking through a library of probability distributions – including the normal distribution, which in turn leads to the C

• edX
• 4 weeks, 6-10 hours a week
• Self-Paced
• Free Online Course (Audit)

VinAI

Robust Parameter Estimation in Computer Vision

Explore robust parameter estimation in computer vision, focusing on algorithms for handling outliers in large-scale data and recent developments in the field.

• YouTube
• 1 hour 13 minutes
• Self-Paced
• Free Video

Statistical Distributions: Wolfram U Class

Build derived, formula, mixture and copula distributions in the Wolfram Language, computing their properties, probabilities, random samples and estimated parameters.

• Wolfram U
• 24 minutes
• Self-Paced
• Free Online Course

Handling Uncertainties and Calibrating System Models with Wolfram Language

Webinar on calibrating system model parameters against real-world data and visualizing output uncertainty, with orbital transfer, chemical reaction and loudspeaker examples.

• Wolfram U
• 1 hour
• Self-Paced
• Free Online Course

Iain Explains Signals, Systems, and Digital Comms

Estimation, Filtering and Prediction

Dive into digital filtering, estimation, and prediction techniques including Kalman filters, least squares estimation, and adaptive algorithms for signal processing applications.

• YouTube
• 1 hour 44 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Logistic Regression: Introduction to Binary Classification and Linear Classifiers

Master logistic regression for binary classification, covering linear classifiers, sigmoid functions, parameter estimation, and log-likelihood functions.

• YouTube
• 29 minutes
• Self-Paced
• Free Video