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Statistics Courses

Statistics courses can help you learn data analysis, probability theory, hypothesis testing, and regression techniques. You can build skills in interpreting data sets, making informed predictions, and conducting surveys. Many courses introduce tools like R, Python, and Excel, that support performing statistical analyses and visualizing results. You'll also explore key topics such as descriptive statistics, inferential statistics, and experimental design, equipping you with the knowledge to tackle real-world data challenges.


Popular Statistics Courses and Certifications


  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Sports Performance Analytics

    Skills you'll gain: Logistic Regression, Forecasting, Regression Analysis, Data Cleansing, Scikit Learn (Machine Learning Library), Supervised Learning, Data Processing, Sports Medicine, Correlation Analysis, Data Preprocessing, Predictive Modeling, Matplotlib, Applied Machine Learning, Statistical Modeling, Injury Prevention, Athletic Training, Analytics, Data Analysis, Statistical Analysis, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    275 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Relational Database Administration (DBA)

    Skills you'll gain: Database Administration, Database Management, Database Architecture and Administration, Relational Databases, Operational Databases, Database Systems, IBM DB2, MySQL, Performance Tuning, PostgreSQL, Disaster Recovery, Data Storage Technologies, Database Design, System Monitoring, Role-Based Access Control (RBAC), User Accounts, Encryption

    4.5
    Rating, 4.5 out of 5 stars
    ·
    257 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    F

    Fractal Analytics

    Python for Data Science

    Skills you'll gain: Feature Engineering, Data Wrangling, Exploratory Data Analysis, Matplotlib, Statistical Analysis, Data Preprocessing, Seaborn, Data Science, Data Visualization Software, Data Manipulation, Data Cleansing, Data Analysis, Pandas (Python Package), Statistics, Business Analytics, Jupyter, Data Transformation, Descriptive Statistics, Correlation Analysis, Statistical Hypothesis Testing

    4.1
    Rating, 4.1 out of 5 stars
    ·
    98 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    W

    Wesleyan University

    Data Analysis and Interpretation

    Skills you'll gain: Regression Analysis, Data Storytelling, Logistic Regression, Classification And Regression Tree (CART), Statistical Hypothesis Testing, Descriptive Statistics, Statistical Analysis, Statistical Software, Correlation Analysis, Exploratory Data Analysis, Data Manipulation, Decision Tree Learning, Data Presentation, Data Management, Data Analysis, Data Visualization, Model Evaluation, Data Literacy, Machine Learning, Statistics

    4.4
    Rating, 4.4 out of 5 stars
    ·
    1.4K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Practical Machine Learning

    Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Supervised Learning, Predictive Analytics, Applied Machine Learning, Data Preprocessing, R Programming, Classification Algorithms, Machine Learning, Random Forest Algorithm, Regression Analysis, Exploratory Data Analysis, Data Wrangling

    4.5
    Rating, 4.5 out of 5 stars
    ·
    3.3K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Machine Learning: Classification

    Skills you'll gain: Classification Algorithms, Applied Machine Learning, Logistic Regression, Supervised Learning, Predictive Modeling, Decision Tree Learning, Data Preprocessing, Model Evaluation, Text Mining, Machine Learning Algorithms, Scalability, Machine Learning, Natural Language Processing, Big Data, Probability & Statistics, Algorithms

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.7K reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    A

    Alberta Machine Intelligence Institute

    Machine Learning Algorithms: Supervised Learning Tip to Tail

    Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Classification Algorithms, Model Evaluation, Jupyter, Decision Tree Learning, Machine Learning, Data Preprocessing, Scikit Learn (Machine Learning Library), Business Solutions, Python Programming, Regression Analysis, Performance Analysis, Feature Engineering, Data Processing, Process Optimization

    4.7
    Rating, 4.7 out of 5 stars
    ·
    417 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Deep Learning and Reinforcement Learning

    Skills you'll gain: Autoencoders, Generative AI, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Unsupervised Learning, Machine Learning Methods, Transfer Learning, Artificial Neural Networks, Keras (Neural Network Library), Machine Learning, Computer Vision, Dimensionality Reduction, Model Evaluation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    285 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    S

    SAS

    SAS Programmer

    Skills you'll gain: Data Manipulation, SAS (Software), Data Access, Data Import/Export, Microsoft Excel, Data Analysis, Data Transformation, Requirements Analysis, Statistical Programming, Exploratory Data Analysis, Data Cleansing, Statistical Analysis, Data Processing, Data Preprocessing, Data Integration, SQL, Descriptive Statistics, Computer Programming, Data Presentation, Debugging

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    3.5K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • U

    Universidad de los Andes

    Fundamentos de probabilidad y aplicaciones

    Skills you'll gain: Probability, Probability Distribution, Applied Mathematics, Statistics, Risk Management, Risk Modeling, Combinatorics, Descriptive Statistics

    4.8
    Rating, 4.8 out of 5 stars
    ·
    178 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    User Experience Research and Design

    Skills you'll gain: UI/UX Research, Surveys, Qualitative Research, Usability Testing, User Experience Design, User Research, User Experience, User Story, Prototyping, Wireframing, User Centered Design, Survey Creation, Sampling (Statistics), Design Research, Interaction Design, Ideation, A/B Testing, Conceptual Design, Web Analytics, Usability

    4.7
    Rating, 4.7 out of 5 stars
    ·
    2.3K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    R

    Real Madrid Graduate School Universidad Europea

    Conceptos imprescindibles - Requisitos para el análisis

    Skills you'll gain: Data Literacy, Technical Communication, Probability & Statistics, Web Scraping, Data Import/Export, JSON, Statistical Analysis, Pandas (Python Package), Analytical Skills, Descriptive Statistics, Data Manipulation, Probability, Data Collection, Data Capture, Restful API, Performance Measurement, Data Cleansing, Application Programming Interface (API)

    Beginner · Course · 1 - 4 Weeks

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

  • Sports Performance Analytics: University of Michigan
  • Relational Database Administration (DBA): IBM
  • Python for Data Science: Fractal Analytics
  • Data Analysis and Interpretation: Wesleyan University
  • Practical Machine Learning: Johns Hopkins University
  • Machine Learning: Classification: University of Washington
  • Machine Learning Algorithms: Supervised Learning Tip to Tail: Alberta Machine Intelligence Institute
  • Deep Learning and Reinforcement Learning: IBM
  • SAS Programmer: SAS
  • Fundamentos de probabilidad y aplicaciones: Universidad de los Andes

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