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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

    • U

      Universidad de los Andes

      Plataformas para procesar datos no tradicionales​

      Skills you'll gain: Spatial Analysis, NoSQL, Spatial Data Analysis, Geospatial Mapping, Geographic Information Systems, Public Cloud, Big Data, MongoDB, Apache Hadoop, Apache Spark, Distributed Computing, Data Architecture, Cloud Services, Data Processing, Cloud Computing, Scalability, Databases, Environmental Monitoring, File Systems, Image Analysis

      4.2
      Rating, 4.2 out of 5 stars
      ·
      10 reviews

      Beginner · Specialization · 3 - 6 Months

    • T

      Tsinghua University

      Data Structures and Algorithms

      Skills you'll gain: Data Structures, Algorithms, Graph Theory, Computational Thinking, Programming Principles, Theoretical Computer Science, Database Design, Query Languages, Spatial Analysis, System Design and Implementation, Computational Logic, Computer Programming

      2.8
      Rating, 2.8 out of 5 stars
      ·
      39 reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IE Business School

      Riesgos y oportunidades empresariales en una economía globalizada

      Skills you'll gain: Economics, Financial Policy, Economic Development, Trend Analysis, Global Marketing, Business Economics, International Relations, Analysis, Socioeconomics, Business Risk Management, Public Policies, Business Strategies, World History, Investments

      4.9
      Rating, 4.9 out of 5 stars
      ·
      101 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      N

      National Taiwan University

      頑想學概率:機率二 (Probability (2))

      Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Advanced Mathematics, Statistical Methods, Calculus

      4.8
      Rating, 4.8 out of 5 stars
      ·
      92 reviews

      Mixed · Course · 1 - 3 Months

    • I

      IBM

      Machine Learning Rapid Prototyping with IBM Watson Studio

      Skills you'll gain: Feature Engineering, Data Transformation, Data Processing, Data Cleansing, Applied Machine Learning, MLOps (Machine Learning Operations), Predictive Modeling, Exploratory Data Analysis, Automation, Machine Learning Methods, Machine Learning, Scikit Learn (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Performance Tuning

      4.2
      Rating, 4.2 out of 5 stars
      ·
      15 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Q

      Queen Mary University of London

      Analysis and Interpretation of Data

      Skills you'll gain: Data Analysis, Statistical Analysis, Correlation Analysis, Quantitative Research, Regression Analysis, Content Performance Analysis, Marketing Analytics, Probability & Statistics, Trend Analysis, Data Cleansing, Digital Marketing, Exploratory Data Analysis, Market Research, Return On Investment

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      S

      Sapienza University of Rome

      Paesaggi di Roma Antica. Archeologia e storia del Palatino.

      Skills you'll gain: Ancient History, Scientific Methods, Research, Research Methodologies, Investigation, Spatial Analysis, Art History, Geographic Information Systems, World History, Data Integration, Culture, Information Systems

      4.8
      Rating, 4.8 out of 5 stars
      ·
      144 reviews

      Beginner · Course · 1 - 3 Months

    • P

      Pontificia Universidad Católica de Chile

      Python para Ciencia de Datos

      Skills you'll gain: Descriptive Analytics, Data-Driven Decision-Making, Data Analysis, Data Visualization Software, Predictive Analytics, Business Analytics, Database Management, Data Science, Relational Databases, Data Processing, Trend Analysis, Forecasting, Data Manipulation, Python Programming

      3.8
      Rating, 3.8 out of 5 stars
      ·
      67 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      AI Workflow: Feature Engineering and Bias Detection

      Skills you'll gain: Feature Engineering, Data Ethics, Unsupervised Learning, Dimensionality Reduction, Text Mining, Applied Machine Learning, Data Transformation, Anomaly Detection, Exploratory Data Analysis, Natural Language Processing, Quality Assurance, Data Validation, Machine Learning Algorithms, Data Visualization

      4.4
      Rating, 4.4 out of 5 stars
      ·
      72 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: New
      New
      M

      Microsoft

      Building Intelligent Troubleshooting Agents

      Skills you'll gain: Large Language Modeling, Natural Language Processing, Generative AI Agents, Prompt Engineering, Test Case, Agentic systems, Human Computer Interaction, Artificial Intelligence and Machine Learning (AI/ML), Debugging, Artificial Intelligence, Performance Tuning, Python Programming, Machine Learning

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Launching into Machine Learning en Español

      Skills you'll gain: Exploratory Data Analysis, Data Quality, Applied Machine Learning, Machine Learning, Supervised Learning, Machine Learning Algorithms, Google Cloud Platform, Data Analysis, Big Data, Sampling (Statistics), Regression Analysis, Performance Tuning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      131 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado System

      Data Analysis and Representation, Selection and Iteration

      Skills you'll gain: Computational Thinking, Data Analysis, C (Programming Language), Statistical Analysis, Programming Principles, Data Structures, Descriptive Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      93 reviews

      Beginner · Course · 1 - 4 Weeks

    Searches related to statistics

    statistics for data science
    statistics with python
    statistics with r
    statistics for data analysis
    statistics for data science with python
    statistics in psychological research
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    1…585960…107

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

    • Plataformas para procesar datos no tradicionales​: Universidad de los Andes
    • Data Structures and Algorithms: Tsinghua University
    • Riesgos y oportunidades empresariales en una economía globalizada: IE Business School
    • 頑想學概率:機率二 (Probability (2)): National Taiwan University
    • Machine Learning Rapid Prototyping with IBM Watson Studio: IBM
    • Analysis and Interpretation of Data: Queen Mary University of London
    • Paesaggi di Roma Antica. Archeologia e storia del Palatino.: Sapienza University of Rome
    • Python para Ciencia de Datos: Pontificia Universidad Católica de Chile
    • AI Workflow: Feature Engineering and Bias Detection: IBM
    • Building Intelligent Troubleshooting Agents: Microsoft

    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.

    Frequently Asked Questions about Statistics

    Top statistics courses include Introduction to Statistics from Stanford University, Business Statistics and Analysis from Rice University, and Statistics with Python from the University of Michigan. These courses cover descriptive statistics, probability, hypothesis testing, and statistical modeling.‎

    Yes. Many statistics courses offer a free audit option, allowing you to access video lessons and reading materials without payment. If you want to complete assignments or earn a certificate, you’ll need to pay or apply for financial aid.‎

    You’ll learn how to collect, interpret, and present data; calculate key metrics like mean and standard deviation; and apply statistical techniques such as regression analysis, probability distributions, and confidence intervals. Some courses also include hands-on practice with Excel, R, or Python.‎

    Not necessarily. Many Coursera statistics courses are designed for beginners and explain core concepts step by step. Some basic comfort with numbers is helpful, but you don’t need advanced math experience to get started.‎

    Yes. Statistics is essential in fields like business, healthcare, data science, psychology, and research. Learning statistics on Coursera can help you analyze data, make informed decisions, and gain skills that are valuable in both academic and professional settings.‎

    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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