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: FreeÉcole normale supérieure
Skills you'll gain: Sampling (Statistics), Physics, Simulations, Computational Logic, Numerical Analysis, Markov Model, Quantitative Research, Algorithms, Applied Mathematics, Linear Algebra, Integral Calculus
Status: Free TrialJohns Hopkins University
Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Probability & Statistics, Statistical Methods, Probability Distribution, Data Analysis, Markov Model, Data Science, Statistics, Statistical Inference, Probability, R Programming
Status: PreviewUniversity of London
Skills you'll gain: Descriptive Statistics, Statistics, Probability & Statistics, Statistical Hypothesis Testing, Data Visualization, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Probability Distribution, Sampling (Statistics), Risk Modeling, Statistical Inference, Mathematical Modeling
Status: Free TrialImperial College London
Skills you'll gain: Tensorflow, Autoencoders, Generative Model Architectures, Deep Learning, Applied Machine Learning, Image Analysis, Bayesian Statistics, Probability Distribution, Unsupervised Learning, Sampling (Statistics)
Status: Free TrialUniversity of Alberta
Skills you'll gain: Reinforcement Learning, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Probability Distribution
28DIGITAL
Skills you'll gain: Computational Logic, Markov Model, Verification And Validation, Theoretical Computer Science, Mathematical Modeling, Systems Analysis, Statistical Modeling, Probability, Algorithms, Probability Distribution
Status: NewArizona State University
Skills you'll gain: Probability & Statistics, Analytical Skills, Exploratory Data Analysis, Estimation, Logistic Regression
Status: NewArizona State University
Skills you'll gain: Bayesian Statistics, Statistical Modeling, Bayesian Network, Statistical Methods, Statistical Analysis, Data Analysis, R Programming, Data-Driven Decision-Making, Statistical Inference, Markov Model, Simulations, Probability Distribution
Status: Free TrialUniversity of Colorado Boulder
Skills you'll gain: Quantitative Research, Engineering Calculations, Mechanical Engineering, Numerical Analysis, Chemistry, Physics, Simulation and Simulation Software, Mathematical Modeling, Differential Equations
Status: NewStatus: PreviewNortheastern University
Skills you'll gain: Probability & Statistics, Probability Distribution, Probability, Statistical Methods, Exploratory Data Analysis, Statistical Analysis, Bayesian Statistics, Descriptive Statistics, Data Analysis, Statistical Visualization, Correlation Analysis, Reliability, Risk Modeling
Status: NewStatus: Free TrialBirla Institute of Technology & Science, Pilani
Skills you'll gain: Data Analysis, Statistical Analysis, Data Visualization, Predictive Modeling, Applied Mathematics
Status: Free TrialUniversity of California, Santa Cruz
Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Bayesian Statistics, Statistical Modeling, R (Software), Statistical Analysis, Statistical Inference, Regression Analysis, Data Analysis, Mathematical Modeling, Model Evaluation
In summary, here are 10 of our most popular stochastic process courses
- Statistical Mechanics: Algorithms and Computations: École normale supérieure
- Advanced Probability and Statistical Methods:Â Johns Hopkins University
- Probability and Statistics: To p or not to p?:Â University of London
- Probabilistic Deep Learning with TensorFlow 2:Â Imperial College London
- Sample-based Learning Methods:Â University of Alberta
- Quantitative Model Checking:Â 28DIGITAL
- Probability, Statistical Inference and Regression Analysis:Â Arizona State University
- Bayesian Statistical Concepts and Methods:Â Arizona State University
- Quantum Mechanics:Â University of Colorado Boulder
- Engineering Probability and Statistics Part 1:Â Northeastern University
