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    • Statistics

    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
      U

      University of California, Davis

      Data Visualization with Tableau

      Skills you'll gain: Dashboard, Data Storytelling, Tableau Software, Data Presentation, Data Visualization, Visual Design, Advanced Analytics, Stakeholder Analysis, Interactive Data Visualization, Data Visualization Software, Design, Data Literacy, Exploratory Data Analysis, Proposal Development, Data Ethics, Data Analysis, Visualization (Computer Graphics), Pivot Tables And Charts, Data Mapping, Storyboarding

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Davis

      Geographic Information Systems (GIS)

      Skills you'll gain: ArcGIS, GIS Software, Spatial Analysis, Data Storytelling, Spatial Data Analysis, Geographic Information Systems, Data Presentation, Geospatial Mapping, Public Health and Disease Prevention, Public Health, Land Management, Geospatial Information and Technology, Heat Maps, Data Sharing, Epidemiology, Community Health, Metadata Management, Data Visualization Software, Data Quality, Network Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Capstone: Retrieving, Processing, and Visualizing Data with Python

      Skills you'll gain: Data Processing, Data Visualization, Data Cleansing, Data Collection, Data Visualization Software, Data Manipulation, Python Programming, Exploratory Data Analysis, Algorithms, Data Analysis, Web Scraping, Database Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Epidemiology in Public Health Practice

      Skills you'll gain: Epidemiology, Public Health, Data Presentation, Public Health and Disease Prevention, Trend Analysis, Geographic Information Systems, Health Policy, Data Visualization Software, Chronic Diseases, GIS Software, Health Systems, Infectious Diseases, Biostatistics, Risk Analysis, Investigation, Health Care, Health Disparities, Community Health, Data Analysis, Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Neuroscience and Neuroimaging

      Skills you'll gain: Magnetic Resonance Imaging, Neurology, Medical Imaging, Diagnostic Radiology, Anatomy, Image Analysis, Data Analysis, X-Ray Computed Tomography, Correlation Analysis, Data Manipulation, Radiology, Analytical Skills, Experimentation, Research Design, Statistical Analysis, Biomedical Technology, Advanced Analytics, Network Analysis, R Programming, Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.3K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      I

      IBM

      IBM Deep Learning with PyTorch, Keras and Tensorflow

      Skills you'll gain: PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Unsupervised Learning, Artificial Neural Networks, Machine Learning Methods, Generative AI, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Image Analysis, Computer Vision, Artificial Intelligence, Machine Learning, Regression Analysis, Network Architecture, Network Model, Predictive Modeling, Natural Language Processing, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      4K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Regression Analysis, Dimensionality Reduction, Reinforcement Learning, Generative Model Architectures, Deep Learning, Data Analysis, Statistical Methods, Statistical Inference, Applied Machine Learning, Predictive Modeling, Statistical Hypothesis Testing, Data Processing, Machine Learning Algorithms, Machine Learning, Data Science, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.3K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations of Data Science

      Skills you'll gain: Data Ethics, Data-Driven Decision-Making, Data Analysis, Analytics, Business Analytics, Data Storytelling, Big Data, Data Science, Communication, Stakeholder Communications, Workflow Management, Project Management, Artificial Intelligence

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Applied Machine Learning in Python

      Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Dimensionality Reduction, Random Forest Algorithm, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.6K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Introduction to Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Regression Analysis, Dimensionality Reduction, Statistical Methods, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Processing, Data Access, Machine Learning, Statistics, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Statistical Analysis, Data Analysis, Applied Machine Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Introduction to Genomic Technologies

      Skills you'll gain: Bioinformatics, Data Science, Molecular Biology, Data Analysis, Computer Science, Statistical Analysis, Computational Thinking, Biostatistics, Statistics, Software Engineering, Algorithms, Biology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.8K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to Software Engineering

      Skills you'll gain: Software Development Life Cycle, Software Architecture, Software Design, Scrum (Software Development), Software Engineering, Software Design Patterns, Agile Methodology, Software Development, Programming Principles, Application Development, Cloud Development, Web Development, Back-End Web Development, Front-End Web Development, Computer Programming, Integrated Development Environments, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4K reviews

      Beginner · Course · 1 - 3 Months

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    1…111213…117

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

    • Data Visualization with Tableau: University of California, Davis
    • Geographic Information Systems (GIS): University of California, Davis
    • Capstone: Retrieving, Processing, and Visualizing Data with Python: University of Michigan
    • Epidemiology in Public Health Practice: Johns Hopkins University
    • Neuroscience and Neuroimaging: Johns Hopkins University
    • IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
    • IBM Machine Learning: IBM
    • Foundations of Data Science: Google
    • Applied Machine Learning in Python: University of Michigan
    • IBM Introduction to Machine Learning: IBM

    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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