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  • Implement Monte Carlo Integration Methods

Results for "implement monte-carlo integration methods"


  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Octave Programming: Analyze, Apply & Implement

    Skills you'll gain: Plot (Graphics), Scripting, Scientific Visualization, Visualization (Computer Graphics), Graphing, Programming Principles, Debugging, Matlab, Computational Thinking, Numerical Analysis, Data Manipulation, Linear Algebra

    Mixed · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    L

    Ludwig-Maximilians-Universität München (LMU)

    Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

    Skills you'll gain: Finite Element Methods, Numerical Analysis, Engineering Analysis, Jupyter, Engineering Calculations, Differential Equations, Applied Mathematics, Mathematical Modeling, Distributed Computing, Python Programming, Mechanics, Vibrations, Simulations

    4.8
    Rating, 4.8 out of 5 stars
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    389 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    C

    Columbia University

    Computational Methods in Pricing and Model Calibration

    Skills you'll gain: Regression Analysis, Actuarial Science, Derivatives, Financial Market, Statistical Methods, Market Data, Financial Modeling, Securities (Finance), Risk Modeling, Financial Systems, Mathematical Modeling, Numerical Analysis, Applied Mathematics, Python Programming, Process Optimization, Probability Distribution, Algorithms, Case Studies

    4.4
    Rating, 4.4 out of 5 stars
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    43 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    J

    Johns Hopkins University

    Advanced Methods in Machine Learning Applications

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Random Forest Algorithm, Decision Tree Learning, Supervised Learning, Logistic Regression, Classification Algorithms

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Statistical Methods for Computer Science

    Skills you'll gain: Network Analysis, R Programming, Statistical Analysis, Regression Analysis, Statistical Modeling, Bayesian Network, Statistical Hypothesis Testing, Statistical Programming, Data Analysis, R (Software), Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Statistical Methods, Social Network Analysis, Applied Mathematics, Simulations, Data Science, Markov Model

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Introduction to Probability and Data with R

    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

    4.7
    Rating, 4.7 out of 5 stars
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    5.9K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Preview
    Preview
    J

    Johns Hopkins University

    Random Processes

    Skills you'll gain: Probability & Statistics, Probability Distribution, Simulations, Statistical Modeling, Correlation Analysis, Engineering Analysis, Digital Signal Processing, Statistical Analysis, Reliability, Engineering, Spatial Analysis

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    B

    Board Infinity

    Machine Learning with Implementation in Java

    Skills you'll gain: Data Preprocessing, Model Deployment, Apache Mahout, Java, Java Programming, Apache Spark, Classification Algorithms, Applied Machine Learning, Deep Learning, Model Evaluation, Natural Language Processing, Data Cleansing, Machine Learning, Feature Engineering, Regression Analysis

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Preview
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    E

    EDUCBA

    Bayesian Statistics: Excel to Python A/B Testing

    Skills you'll gain: Bayesian Statistics, A/B Testing, Microsoft Excel, Statistical Machine Learning, Statistical Modeling, Predictive Analytics, Business Analytics, Data Analysis, Advanced Analytics, Probability & Statistics, Decision Making, Health Informatics, Statistical Programming, Markov Model

    Mixed · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Advanced Data Science Techniques (with AWS Integration)

    Skills you'll gain: AWS SageMaker, Unsupervised Learning, Feature Engineering, Time Series Analysis and Forecasting, Model Deployment, Cloud Deployment, Amazon Web Services, Applied Machine Learning, Amazon Redshift, Machine Learning Methods, Amazon S3, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Model Evaluation, Forecasting, MLOps (Machine Learning Operations), Predictive Analytics, Data Preprocessing, Supervised Learning, Dimensionality Reduction

    Beginner · Course · 1 - 3 Months

  • U

    University of Colorado Boulder

    Introduction to Bayesian Statistics for Data Science

    Skills you'll gain: Bayesian Statistics, Statistical Inference, Statistical Modeling, Predictive Analytics, Statistical Methods, Data Ethics, Data Science, Probability, Regression Analysis, Probability Distribution, Calculus

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    C

    Coursera

    Innovate with ANSYS Simulation Tools

    Skills you'll gain: Engineering Design Process, Engineering Analysis, Mechanical Design, Simulation and Simulation Software, Structural Analysis, Mechanical Engineering, Numerical Analysis, Finite Element Methods, Materials science

    4.9
    Rating, 4.9 out of 5 stars
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    31 reviews

    Beginner · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular implement monte-carlo integration methods courses

  • Octave Programming: Analyze, Apply & Implement: EDUCBA
  • Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python: Ludwig-Maximilians-Universität München (LMU)
  • Computational Methods in Pricing and Model Calibration: Columbia University
  • Advanced Methods in Machine Learning Applications: Johns Hopkins University
  • Statistical Methods for Computer Science: Johns Hopkins University
  • Introduction to Probability and Data with R: Duke University
  • Random Processes: Johns Hopkins University
  • Machine Learning with Implementation in Java: Board Infinity
  • Bayesian Statistics: Excel to Python A/B Testing: EDUCBA
  • Advanced Data Science Techniques (with AWS Integration): Coursera

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