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    Statistics Courses

    Statistics courses can help you learn how to collect, analyze, and interpret data to make informed decisions in fields like science, business, and healthcare.

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    Find the Best Statistics Course for Your Goals

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science

      Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Wrangling, Data Visualization, Machine Learning Algorithms, Plotly, Machine Learning, GitHub

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Applied Software Engineering Fundamentals

      Skills you'll gain: Software Development Life Cycle, Software Architecture, Linux Commands, Bash (Scripting Language), Shell Script, Git (Version Control System), GitHub, Flask (Web Framework), Software Design, Unit Testing, Version Control, File Management, Jupyter, Unix Shell, Scrum (Software Development), Software Engineering, Linux, Application Deployment, Python Programming, Data Structures

      4.6
      Rating, 4.6 out of 5 stars
      ·
      49K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Databricks

      Introduction to Computational Statistics for Data Scientists

      Skills you'll gain: Bayesian Statistics, Databricks, Sampling (Statistics), Statistical Modeling, Probability, Classification And Regression Tree (CART), Jupyter, Regression Analysis, Statistical Programming, Predictive Modeling, Statistical Analysis, Statistical Machine Learning, Probability Distribution, Data Science, Markov Model, Statistics, Simulations, Python Programming, Mathematical Software, Statistical Inference

      4
      Rating, 4 out of 5 stars
      ·
      109 reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: New
      New
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      N

      Northeastern University

      Engineering Probability and Statistics Part 2

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Statistical Reporting, Probability & Statistics, Statistical Methods, Statistical Analysis, Data Analysis, Estimation, Data Presentation, Descriptive Statistics

      Mixed · Course · 1 - 3 Months

    • Status: New
      New
      Status: Preview
      Preview
      N

      Northeastern University

      Engineering Probability and Statistics Part 1

      Skills you'll gain: Probability & Statistics, Probability Distribution, Probability, Statistical Modeling, Exploratory Data Analysis, Statistical Analysis, Bayesian Statistics, Descriptive Statistics, Data Analysis, Correlation Analysis, Reliability

      Mixed · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      U

      University of Pittsburgh

      Statistics and Calculus Methods for Data Analysis

      Skills you'll gain: Statistical Analysis, Statistical Modeling, Predictive Modeling, Data Analysis, Statistics, Integral Calculus, Probability & Statistics, Data Science, Probability Distribution, Calculus, Mathematics and Mathematical Modeling, Applied Mathematics, Derivatives, Probability, Mathematical Modeling, Pandas (Python Package), Machine Learning, Algorithms

      Build toward a degree

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Preview
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      N

      Northeastern University

      Statistical Learning for Engineering Part 2

      Skills you'll gain: PyTorch (Machine Learning Library), Applied Machine Learning, Unsupervised Learning, Reinforcement Learning, Supervised Learning, Machine Learning Algorithms, Machine Learning Methods, Dimensionality Reduction, Statistical Machine Learning, Machine Learning, Machine Learning Software, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification And Regression Tree (CART), Decision Tree Learning, Generative AI, Random Forest Algorithm, Predictive Modeling, Feature Engineering

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Preview
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      N

      Northeastern University

      Statistical Learning for Engineering Part 1

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Statistical Modeling, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Statistical Programming, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Probability & Statistics, Dimensionality Reduction

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Linear Regression for Business Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Regression Analysis, Statistical Analysis, Statistical Modeling, Statistical Inference, Business Analytics, Microsoft Excel, Estimation, Data Analysis, Data Transformation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.4K reviews

      Mixed · 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, Statistical Analysis, Statistical Inference, Regression Analysis, Data Analysis, Mathematical Modeling, Probability Distribution

      4.2
      Rating, 4.2 out of 5 stars
      ·
      17 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of London

      Statistics and Clustering in Python

      Skills you'll gain: Pandas (Python Package), NumPy, Probability & Statistics, Unsupervised Learning, Data Science, Statistics, Data Analysis, Statistical Analysis, Jupyter, Data Manipulation, Machine Learning Algorithms, Descriptive Statistics, Matplotlib, Data Visualization Software, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Business Statistics and Analysis Capstone

      Skills you'll gain: Statistical Analysis, Data Analysis, Data Presentation, Statistics, Business Analysis, Statistical Reporting, Analytical Skills, Technical Communication, Predictive Analytics, Exploratory Data Analysis, Regression Analysis, Microsoft Excel, Data Manipulation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      437 reviews

      Mixed · Course · 1 - 4 Weeks

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    1…8910…112

    In summary, here are 10 of our most popular statistics courses

    • Data Science: Johns Hopkins University
    • Applied Software Engineering Fundamentals: IBM
    • Introduction to Computational Statistics for Data Scientists: Databricks
    • Engineering Probability and Statistics Part 2: Northeastern University
    • Engineering Probability and Statistics Part 1: Northeastern University
    • Statistics and Calculus Methods for Data Analysis: University of Pittsburgh
    • Statistical Learning for Engineering Part 2: Northeastern University
    • Statistical Learning for Engineering Part 1: Northeastern University
    • Linear Regression for Business Statistics: Rice University
    • Bayesian Statistics: Time Series Analysis: University of California, Santa Cruz

    Why Learn Statistics?

    Statistics is the science of collecting, analyzing, and interpreting data to uncover patterns and inform decisions. It’s essential in fields like business, healthcare, social science, and data analytics. Learning statistics can help you make sense of data, support evidence-based thinking, and contribute to smarter outcomes in any field.

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