Stochastic Process Courses
Courses in stochastic processes can help you learn about Markov chains, Poisson processes, and Brownian motion, along with their applications in fields like finance and telecommunications. You can build skills in analyzing random systems, modeling uncertainty, and predicting future events based on historical data. Many courses introduce tools such as MATLAB and R, that support simulating stochastic models and performing statistical analysis, enabling you to apply your knowledge in practical scenarios.
Popular Stochastic Process Courses and Certifications
Status: PreviewJohns Hopkins University
Skills you'll gain: Probability, Bayesian Statistics, Probability Distribution, Risk Modeling, Mathematical Modeling, Statistical Inference, Markov Model, Reliability, Simulations, Applied Mathematics, Statistical Analysis, Regression Analysis
Status: Free TrialIllinois Tech
Skills you'll gain: Bayesian Statistics, Data Analysis, Statistical Inference, Regression Analysis, Statistical Analysis, Statistical Modeling, Statistical Programming, Sampling (Statistics), R Programming, Markov Model, Logistic Regression, Probability, Simulations, Model Evaluation, Probability Distribution
Status: Free TrialUniversity of Colorado System
Skills you'll gain: Bayesian Network, Numerical Analysis, Estimation, Simulations, Matlab, Mathematical Modeling, Applied Mathematics, Engineering Analysis, Algorithms
Status: Free TrialDuke University
Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, R (Software), Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Descriptive Statistics
Status: PreviewCarnegie Mellon University
Skills you'll gain: Mechanical Engineering, Chemical Engineering, Engineering, Materials science, Chemistry, Physics, Molecular, Cellular, and Microbiology, Mathematical Modeling, Physical Science, Biology
Skills you'll gain: Statistical Inference, Probability Distribution, R Programming, Statistical Visualization, Statistics, Data Visualization, Statistical Analysis, Statistical Modeling, Statistical Hypothesis Testing, Data Analysis, Probability
Status: PreviewUniversity of Leeds
Skills you'll gain: Exploratory Data Analysis, Statistical Methods, Statistical Modeling, R (Software), Data Collection, Statistical Inference, Probability, Data Analysis, Statistical Analysis, Probability Distribution, Simulations, Statistical Visualization, Descriptive Statistics, Sampling (Statistics), Data Visualization Software
Status: NewStatus: Free TrialDartmouth College
Skills you'll gain: Classification Algorithms
Duke University
Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Analysis, Regression Analysis, Data Analysis, R Programming, Probability, Probability Distribution
Status: Free TrialUniversity of California, Santa Cruz
Skills you'll gain: R Programming, Statistical Modeling, Bayesian Statistics, Statistical Software, Markov Model, Mathematical Modeling, Statistical Methods, Probability & Statistics, Unsupervised Learning, Machine Learning Methods, Probability Distribution, Classification Algorithms
Status: Free TrialUniversità di Napoli Federico II
Skills you'll gain: Derivatives, Financial Market, Securities (Finance), Financial Trading, Finance, Actuarial Science, Investments, Futures Exchange, Equities, Risk Modeling, Financial Modeling, Numerical Analysis, Mathematical Modeling, Simulation and Simulation Software, Probability
Status: PreviewNational Taiwan University
Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Statistics, Data Literacy
In summary, here are 10 of our most popular stochastic process courses
- Introduction to Uncertainty Quantification:Â Johns Hopkins University
- Bayesian Computational Statistics:Â Illinois Tech
- Particle Filters (and Navigation):Â University of Colorado System
- Introduction to Probability and Data with R:Â Duke University
- Statistical Thermodynamics: Molecules to Machines:Â Carnegie Mellon University
- Using probability distributions for real world problems in R:Â Coursera
- Statistical Methods:Â University of Leeds
- Foundations for Machine Learning:Â Dartmouth College
- Bayesian Statistics:Â Duke University
- Bayesian Statistics: Mixture Models:Â University of California, Santa Cruz
