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    • Applied Statistics

    Applied Statistics Courses Online

    Understand applied statistics for data analysis and interpretation. Learn statistical methods and tools for various industries.

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    Explore the Applied Statistics Course Catalog

    • Status: New
      New
      Status: Preview
      Preview
      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
      U

      University of Washington

      Machine Learning

      Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Probabilistic Graphical Models 2: Inference

      Skills you'll gain: Bayesian Network, Bayesian Statistics, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms, Computational Thinking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      488 reviews

      Advanced · Course · 1 - 3 Months

    • 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
      S

      Stanford University

      Probabilistic Graphical Models 1: Representation

      Skills you'll gain: Bayesian Network, Graph Theory, Probability Distribution, Statistical Modeling, Markov Model, Decision Support Systems, Probability & Statistics, Network Analysis, Applied Machine Learning, Natural Language Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.4K reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Six Sigma Black Belt

      Skills you'll gain: Statistical Process Controls, Lean Six Sigma, Six Sigma Methodology, Lean Methodologies, Process Improvement, Team Management, Process Capability, Lean Manufacturing, Data Collection, Knowledge Transfer, Team Building, Statistical Hypothesis Testing, Meeting Facilitation, Quality Improvement, Continuous Improvement Process, Performance Measurement, Conflict Management, Process Analysis, Sampling (Statistics), Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      769 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Engineering

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

      University of Washington

      Machine Learning: Regression

      Skills you'll gain: Regression Analysis, Predictive Modeling, Supervised Learning, Statistical Modeling, Applied Machine Learning, Predictive Analytics, Feature Engineering, Machine Learning, Statistical Methods, Python Programming, Data Manipulation, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.6K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      DeepLearning.AI TensorFlow Developer

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Keras (Neural Network Library), Natural Language Processing, Time Series Analysis and Forecasting, Deep Learning, Artificial Neural Networks, Generative AI, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Predictive Modeling, Text Mining, Forecasting, Data Processing, Machine Learning, Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      25K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      P

      Pearson

      Data Science Fundamentals Part 1: Unit 1

      Skills you'll gain: Applied Machine Learning, Data Science, Python Programming, Scikit Learn (Machine Learning Library), NumPy, Computational Thinking, Pandas (Python Package), Machine Learning, Data Analysis, Exploratory Data Analysis, Programming Principles, Data Manipulation

      Beginner · Course · 1 - 4 Weeks

    • Status: Preview
      Preview
      U

      Universidad de los Andes

      Fundamentos de estadística aplicada

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

      4.5
      Rating, 4.5 out of 5 stars
      ·
      136 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Illinois Urbana-Champaign

      Managerial Economics and Business Analysis

      Skills you'll gain: Descriptive Statistics, Supply And Demand, Market Dynamics, Sampling (Statistics), Statistical Inference, Business Analytics, Financial Systems, Financial Policy, Banking, Probability Distribution, Analytics, Statistical Analysis, Statistics, Regression Analysis, Data-Driven Decision-Making, Microsoft Excel, Business Mathematics, Statistical Methods, Economics, Statistical Hypothesis Testing

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.2K reviews

      Beginner · Specialization · 3 - 6 Months

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    1…192021…214

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

    • Statistical Learning for Engineering Part 1: Northeastern University
    • Machine Learning: University of Washington
    • Probabilistic Graphical Models 2: Inference: Stanford University
    • Data Science: Johns Hopkins University
    • Probabilistic Graphical Models 1: Representation: Stanford University
    • Six Sigma Black Belt: Kennesaw State University
    • IBM AI Engineering: IBM
    • Machine Learning: Regression: University of Washington
    • DeepLearning.AI TensorFlow Developer: DeepLearning.AI
    • Data Science Fundamentals Part 1: Unit 1: Pearson

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