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    • Statistical Modeling

    Statistical Modeling Courses Online

    Master statistical modeling for predictive analytics. Learn to build and validate models for various types of data.

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    Explore the Statistical Modeling Course Catalog

    • Status: Free Trial
      Free Trial

      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Regression Analysis, Statistical Modeling, Data Ethics, Statistical Methods, R Programming, Statistics, Data Science, Statistical Analysis, Predictive Modeling, Probability & Statistics, Data Modeling, Quantitative Research, Correlation Analysis, Advanced Analytics, Data Analysis, Mathematical Modeling, Machine Learning, Linear Algebra

      Build toward a degree

      4.1
      Rating, 4.1 out of 5 stars
      ·
      52 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial

      University of California, Santa Cruz

      Bayesian Statistics

      Skills you'll gain: Bayesian Statistics, Time Series Analysis and Forecasting, R Programming, Statistical Methods, Data Presentation, Forecasting, Predictive Modeling, Statistical Inference, Statistical Modeling, Markov Model, Probability, Probability & Statistics, Statistical Machine Learning, Data Analysis, Statistical Analysis, Regression Analysis, Statistics, Unsupervised Learning, Probability Distribution, Data Science

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial

      University of Pennsylvania

      Fundamentals of Quantitative Modeling

      Skills you'll gain: Risk Modeling, Mathematical Modeling, Regression Analysis, Predictive Modeling, Business Modeling, Financial Modeling, Predictive Analytics, Process Optimization, Risk Management, Data-Driven Decision-Making, Markov Model, Business Process Improvement, Simulation and Simulation Software, Probability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.2K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      Multiple educators

      Machine Learning

      Skills you'll gain: Unsupervised Learning, Machine Learning, Anomaly Detection, Reinforcement Learning, Supervised Learning, Feature Engineering, Decision Tree Learning, Classification And Regression Tree (CART), Data Ethics, Tensorflow, Regression Analysis, Machine Learning Algorithms, Applied Machine Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Python Programming, NumPy, Artificial Neural Networks

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      35K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      IBM

      IBM AI Engineering

      Skills you'll gain: Prompt Engineering, Large Language Modeling, Unsupervised Learning, PyTorch (Machine Learning Library), Keras (Neural Network Library), Supervised Learning, Applied Machine Learning, Generative AI, Deep Learning, Natural Language Processing, Reinforcement Learning, Scikit Learn (Machine Learning Library), Regression Analysis, Generative AI Agents, Artificial Neural Networks, Machine Learning Algorithms, ChatGPT, Machine Learning, Python Programming, Data Science

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      21K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial

      Stanford University

      Probabilistic Graphical Models

      Skills you'll gain: Bayesian Network, Statistical Modeling, Markov Model, Probability Distribution, Graph Theory, Network Model, Decision Support Systems, Data-Driven Decision-Making, Probability & Statistics, Statistical Machine Learning, Sampling (Statistics), Statistical Inference, Unsupervised Learning, Supervised Learning, Machine Learning, Machine Learning Methods, Network Analysis, Statistical Methods, Algorithms, Computational Thinking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

    What brings you to Coursera today?

    • Status: Preview
      Preview

      Stanford University

      Introduction to Statistics

      Skills you'll gain: Statistics, Descriptive Statistics, Probability & Statistics, Statistical Analysis, Data Analysis, Statistical Methods, Statistical Modeling, Statistical Inference, Sampling (Statistics), Statistical Hypothesis Testing, Data Science, Regression Analysis, Exploratory Data Analysis, Probability, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.2K reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial

      Case Western Reserve University

      Practical Geospatial Geostatistical Modeling

      Skills you'll gain: Exploratory Data Analysis, Spatial Analysis, Spatial Data Analysis, Box Plots, Statistical Modeling, Geospatial Information and Technology, Data Visualization, Geographic Information Systems, R Programming, Data Integration, Descriptive Statistics, Data Validation, Statistical Analysis, Data Transformation, Statistical Methods, Data Analysis, Simulations, Rmarkdown, Data Cleansing, Plot (Graphics)

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial

      Johns Hopkins University

      Statistical Inference

      Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Statistical Analysis, Statistical Methods, Statistical Modeling, Statistics, Probability & Statistics, Probability, Probability Distribution, Sampling (Statistics)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      4.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      University of Pennsylvania

      Business and Financial Modeling

      Skills you'll gain: Risk Modeling, Probability Distribution, Mathematical Modeling, Regression Analysis, Portfolio Management, Predictive Modeling, Business Modeling, Spreadsheet Software, Financial Modeling, Financial Statements, Predictive Analytics, Process Optimization, Financial Statement Analysis, Capital Budgeting, Financial Forecasting, Decision Making, Peer Review, Google Sheets, Return On Investment, Microsoft Excel

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial

      Google

      Google AI Essentials

      Skills you'll gain: Prompt Engineering, Generative AI, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Productivity Software, Workforce Development, Applied Machine Learning, Business Solutions, Organizational Strategy, Business Process Automation, Social Studies, Innovation, Data Collection, Automation, Data Security, Human Machine Interfaces, Forecasting, Emerging Technologies, Analysis, Critical Thinking

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.5K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial

      Case Western Reserve University

      Case Studies in Geostatistical Modeling

      Skills you'll gain: Geostatistics, Spatial Analysis, Exploratory Data Analysis, Geospatial Information and Technology, Data Integration, Statistical Modeling, Statistical Analysis, Data Analysis, Sampling (Statistics), Estimation, Data Cleansing, Data Processing, Simulation and Simulation Software

      Intermediate · Course · 1 - 3 Months

    Statistical Modeling learners also search

    Data Modeling
    Statistical Analysis
    Predictive Modeling
    Predictive Analytics
    Advanced R Programming
    Statistical Inference
    Statistics
    Beginner Predictive Analytics
    1234…325

    In summary, here are 10 of our most popular statistical modeling courses

    • Statistical Modeling for Data Science Applications: University of Colorado Boulder
    • Bayesian Statistics: University of California, Santa Cruz
    • Fundamentals of Quantitative Modeling: University of Pennsylvania
    • Machine Learning: DeepLearning.AI
    • IBM AI Engineering: IBM
    • Probabilistic Graphical Models: Stanford University
    • Introduction to Statistics: Stanford University
    • Practical Geospatial Geostatistical Modeling: Case Western Reserve University
    • Statistical Inference: Johns Hopkins University
    • Business and Financial Modeling: University of Pennsylvania

    Skills you can learn in Probability And Statistics

    R Programming (19)
    Inference (16)
    Linear Regression (12)
    Statistical Analysis (12)
    Statistical Inference (11)
    Regression Analysis (10)
    Biostatistics (9)
    Bayesian (7)
    Logistic Regression (7)
    Probability Distribution (7)
    Bayesian Statistics (6)
    Medical Statistics (6)

    Frequently Asked Questions about Statistical Modeling

    Statistical modeling is the process of using statistics to analyze data and make it usable for decision-making and analysis. It involves using computer programs to pull out numbers from data sets, identify trends, make predictions, and understand different situations. Most statistical modeling results in charts, graphs, or other types of reports to explain the data.‎

    It's important to learn statistical modeling for many reasons to comprehend related material as a student and fulfill work-related requirements. Students often need to learn it because it's used in many different academic fields to understand the material. Many occupations either involve doing statistical analysis or being able to use the output in order to make decisions. Because of the way that data is reported in the media, it's helpful for members of the general public to have some understanding of how statistical modeling works.‎

    Typical careers that use statistical modeling are medical research, scientific research, and financial analysis, but it is a component of many different fields. People working in marketing and sales use statistical modeling to build forecasts and generate prospects. Business managers use it to make decisions and to share information. Academics use it to understand trends and patterns in their fields. Journalists use statistical modeling to present information in their stories. By turning data into usable information, including charts and graphs, statistical modeling can add value to many different fields. People who understand the fundamentals of quantitative modeling and statistical model can expect the skill to enhance their careers.‎

    Taking online courses on Coursera can help you learn statistical modeling in different ways, depending on your interests and needs. Some courses cover the fundamentals of statistics, which may be helpful if you have little background in the area. Others look at how statistical modeling is done with different software packages, such as Python, Excel, or SAS. Many classes focus on the uses of statistical modeling in specific fields, such as artificial intelligence, finance, or history. All classes include projects that help you apply what you learn.‎

    Online Statistical Modeling courses offer a convenient and flexible way to enhance your knowledge or learn new Statistical Modeling skills. Choose from a wide range of Statistical Modeling courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Statistical Modeling, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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