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  • Causal Inference

Causal Inference Courses

Causal inference courses can help you learn statistical techniques, experimental design, and observational study methods. You can build skills in identifying causal relationships, analyzing data sets, and interpreting results to inform decision-making. Many courses introduce tools like R, Python, and specialized software for conducting causal analyses, enabling you to apply these skills in real-world contexts such as public health, economics, and social sciences.


Popular Causal Inference Courses and Certifications


  • Status: New
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    U

    University of Pittsburgh

    Mathematical Foundations for Data Science and Analytics

    Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Statistics, Pandas (Python Package), Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning

    Build toward a degree

    Beginner · Specialization · 1 - 3 Months

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    R

    Real Madrid Graduate School Universidad Europea

    Theoretical Bases of Health and Injury Management

    Skills you'll gain: Kinesiology, Applied Machine Learning, Bayesian Network, Machine Learning, Data-Driven Decision-Making, Epidemiology, Load Balancing, Health Education, Data Integration, Systems Engineering, Psychological Evaluations

    Beginner · Course · 1 - 4 Weeks

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    U

    University of Pittsburgh

    Probability Theory and Regression for Predictive Analytics

    Skills you'll gain: Probability Distribution, Data Science, Probability & Statistics, Predictive Analytics, Probability, Statistical Modeling, Data Analysis, Regression Analysis, Logistic Regression, Statistical Analysis, Statistical Methods, Statistical Machine Learning, Bayesian Statistics, Statistical Inference, Feature Engineering, Applied Mathematics, Python Programming, Machine Learning, Algorithms

    Build toward a degree

    Beginner · Course · 1 - 4 Weeks

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    D

    Duke University

    Data Modeling and Prediction with R

    Skills you'll gain: Data-Driven Decision-Making, Logistic Regression, Statistical Modeling, Model Evaluation, Predictive Modeling, Regression Analysis, R Programming, Statistics, Data Analysis, Probability & Statistics, Statistical Inference

    Beginner · Course · 1 - 4 Weeks

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    P

    Packt

    Eye Tracking the User Experience: From Design to Analysis

    Skills you'll gain: User Experience, UI/UX Research, User Experience Design, Usability Testing, Design Research, Data Visualization, Usability, User Centered Design, User Research, Interactive Data Visualization, Data Analysis, Qualitative Research, Quantitative Research, Data Preprocessing, Statistical Inference

    Beginner · Course · 3 - 6 Months

  • Status: Free Trial
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    D

    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Machine Learning Algorithms, Data Preprocessing, Machine Learning, Machine Learning Methods

    4.6
    Rating, 4.6 out of 5 stars
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    3.1K reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
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    Databricks

    Introduction to Computational Statistics for Data Scientists

    Skills you'll gain: Bayesian Statistics, Databricks, Sampling (Statistics), Statistical Modeling, Probability, Applied Machine Learning, Jupyter, Regression Analysis, Statistical Programming, Predictive Modeling, Statistical Analysis, Model Evaluation, Probability Distribution, Data Science, Logistic Regression, Markov Model, Statistics, Statistical Methods, Simulations, Python Programming

    4
    Rating, 4 out of 5 stars
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    109 reviews

    Beginner · Specialization · 1 - 3 Months

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    B

    Birla Institute of Technology & Science, Pilani

    Probability and Statistics

    Skills you'll gain: Data Analysis, Statistical Analysis, Data Visualization, Predictive Modeling, Applied Mathematics

    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: Free Trial
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    J

    Johns Hopkins University

    Data Science Decisions in Time: Using Causal Information

    Skills you'll gain: Precision Medicine, Clinical Trials, Data Analysis, Data-Driven Decision-Making, Analytics, Data Science, Strategic Decision-Making, Decision Making, Health Policy, Random Forest Algorithm, Personalized Service, A/B Testing, Machine Learning, Online Advertising

    Intermediate · Course · 1 - 3 Months

  • G

    Google Cloud

    Deploy and Scale AI Models with Cloud Run

    Skills you'll gain: Google Cloud Platform, Model Deployment, Serverless Computing, Cloud Deployment, Generative AI, MLOps (Machine Learning Operations), Containerization, Performance Tuning, Scalability

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of California, Santa Cruz

    Bayesian Statistics: Time Series Analysis

    Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Bayesian Statistics, Statistical Modeling, R (Software), Statistical Inference, Regression Analysis, Data Analysis, Mathematical Modeling, Probability Distribution

    4.2
    Rating, 4.2 out of 5 stars
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    17 reviews

    Intermediate · Course · 1 - 3 Months

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In summary, here are 10 of our most popular causal inference courses

  • Mathematical Foundations for Data Science and Analytics: University of Pittsburgh
  • Theoretical Bases of Health and Injury Management : Real Madrid Graduate School Universidad Europea
  • Probability Theory and Regression for Predictive Analytics: University of Pittsburgh
  • Data Modeling and Prediction with R: Duke University
  • Eye Tracking the User Experience: From Design to Analysis: Packt
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Introduction to Computational Statistics for Data Scientists: Databricks
  • Probability and Statistics: Birla Institute of Technology & Science, Pilani
  • Introduction to Bayesian Statistics for Data Science: University of Colorado Boulder
  • Data Science Decisions in Time: Using Causal Information: Johns Hopkins University

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