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    • Causal Inference

    Causal Inference Courses Online

    Explore causal inference methods for determining cause-and-effect relationships. Learn to apply statistical techniques to identify causality in data.

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    Explore the Causal Inference Course Catalog

    • Status: New
      New
      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, Statistical Machine Learning, Probability, Data Science, Regression Analysis, Probability Distribution

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Aerial Image Segmentation with PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Image Analysis, Computer Vision, Deep Learning, Python Programming

      4
      Rating, 4 out of 5 stars
      ·
      29 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      S

      Scrimba

      Open-source AI Models

      Skills you'll gain: Data Ethics, Open Source Technology, Generative AI, Large Language Modeling, Web Development Tools, JavaScript Frameworks, Natural Language Processing

      4.9
      Rating, 4.9 out of 5 stars
      ·
      25 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      Illinois Tech

      Linear Regression

      Skills you'll gain: R Programming, Regression Analysis, Statistical Inference, Statistical Modeling, Statistical Analysis, Predictive Modeling, Data Analysis, Probability & Statistics, Linear Algebra, Mathematical Modeling, Supervised Learning

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      26 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      From Data to Decisions: Finding Patterns with AI

      Skills you'll gain: Statistical Methods, Exploratory Data Analysis, Data Visualization, Generative AI, Statistical Analysis, Histogram, Box Plots, Descriptive Statistics, Data Analysis, Artificial Intelligence, Statistical Inference

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Computational and Graphical Models in Probability

      Skills you'll gain: Bayesian Network, Network Analysis, Simulations, Statistical Modeling, R Programming, Probability Distribution, Graph Theory, Probability & Statistics, Statistical Analysis, Machine Learning, Data Visualization, Statistical Hypothesis Testing

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      L

      LearnKartS

      Introduction to AI and Machine Learning

      Skills you'll gain: AWS SageMaker, Artificial Intelligence, Machine Learning, Applied Machine Learning, Amazon Elastic Compute Cloud, Computer Vision, Natural Language Processing, Amazon S3, Serverless Computing, Reinforcement Learning, Data Wrangling

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Statistics for Data Science Essentials

      Skills you'll gain: Probability, Probability & Statistics, Sampling (Statistics), Probability Distribution, Statistics, Data Science, Statistical Inference, Descriptive Statistics, Statistical Analysis, General Mathematics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Snowflake for Data Science: Intro to Snowpark ML for Python

      Skills you'll gain: Applied Machine Learning, Scikit Learn (Machine Learning Library), MLOps (Machine Learning Operations), Predictive Modeling, Machine Learning, Data Processing, Data Science, Python Programming, Data Transformation, Regression Analysis

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Preview
      Preview
      J

      Johns Hopkins University

      Introduction to Uncertainty Quantification

      Skills you'll gain: Probability, Failure Analysis, Bayesian Statistics, Probability & Statistics, Risk Modeling, Mathematical Modeling, Estimation, Numerical Analysis, Statistical Methods, Reliability, Statistical Inference, Analysis, Simulations, Applied Mathematics, Sampling (Statistics), Regression Analysis

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Preview
      Preview
      U

      University of Glasgow

      Knowledge-First Social Epistemology

      Skills you'll gain: Research, Media and Communications, Peer Review, Social Sciences, Investigation, Probability & Statistics

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      Linear Kalman Filter Deep Dive (and Target Tracking)

      Skills you'll gain: Advanced Mathematics, Anomaly Detection, Systems Of Measurement, Linear Algebra, Mathematical Modeling, Continuous Monitoring, Applied Mathematics, Numerical Analysis, Predictive Analytics, Statistical Methods, Probability & Statistics

      Intermediate · Course · 1 - 4 Weeks

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

    • Introduction to Bayesian Statistics for Data Science: University of Colorado Boulder
    • Aerial Image Segmentation with PyTorch : Coursera Project Network
    • Open-source AI Models: Scrimba
    • Linear Regression: Illinois Tech
    • From Data to Decisions: Finding Patterns with AI: Vanderbilt University
    • Computational and Graphical Models in Probability: Johns Hopkins University
    • Introduction to AI and Machine Learning: LearnKartS
    • Statistics for Data Science Essentials: University of Pennsylvania
    • Snowflake for Data Science: Intro to Snowpark ML for Python: Coursera Project Network
    • Introduction to Uncertainty Quantification: Johns Hopkins University

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