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    Results for "bayesian statistics"

    • I

      Imperial College London

      Master of Science in Machine Learning and Data Science

      Skills you'll gain: Data Ethics, Supervised Learning, Exploratory Data Analysis, Unsupervised Learning, Student Support and Services, PySpark, Data Pipelines, Linear Algebra, Ggplot2, Dimensionality Reduction, Student Services, Data Processing, Big Data, Agentic systems, Graphing, A/B Testing, Unstructured Data, Deep Learning, Bayesian Statistics, Applied Machine Learning

      Earn a degree

      Degree · 1 - 4 Years

    • U

      University of Michigan

      Master of Applied Data Science

      Skills you'll gain: Data Ethics, Data Storytelling, Database Design, Reinforcement Learning, Supervised Learning, Experimentation, PySpark, Interactive Data Visualization, Pandas (Python Package), Network Analysis, Deep Learning, Cloud Services, Natural Language Processing, JSON, Data Mining, Qualitative Research, Statistical Visualization, Unsupervised Learning, Applied Machine Learning, Time Series Analysis and Forecasting

      Earn a degree

      Degree · 1 - 4 Years

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Exploratory Data Analysis and Visualization

      Skills you'll gain:

      Beginner · Course

    • U

      University of Colorado Boulder

      Data Science Graduate Certificate

      Skills you'll gain: Data Mining, Statistical Modeling, Unsupervised Learning, Supervised Learning, Service Level, Deep Learning, Machine Learning Algorithms, Statistical Inference, Performance Testing, Statistical Hypothesis Testing, Dimensionality Reduction, Probability, Applied Machine Learning, Data Warehousing, Statistical Machine Learning, Probability & Statistics, Data Pipelines, Data Processing, Bash (Scripting Language), Data Science

      Credit offered

      Graduate Certificate · 6 - 12 Months

    • O

      O.P. Jindal Global University

      MBA Business Analytics

      Skills you'll gain: Design Thinking, Data Storytelling, Operations Management, Active Listening, Data Visualization, Environmental Social And Corporate Governance (ESG), Working Capital, Financial Statement Analysis, Database Management, Sampling (Statistics), Project Estimation, Business Analytics, Global Marketing, Predictive Analytics, Human Resources Management and Planning, Internet Of Things, Big Data, Regression Analysis, Employee Performance Management, Marketing

      Earn a degree

      Degree · 1 - 4 Years

    • P

      Pontificia Universidad Católica de Chile

      Magíster en Business Analytics

      Skills you'll gain: Customer Analysis, Descriptive Analytics, Revenue Management, FinTech, Web Scraping, People Analytics, Time Series Analysis and Forecasting, Biostatistics, Predictive Analytics, Statistical Reporting, Cloud Security, Data Ethics, Governance, Risk Analysis, Network Analysis, Digital Transformation, Dimensionality Reduction, Sampling (Statistics), Peer Review, Predictive Modeling

      Earn a degree

      Degree · 1 - 4 Years

    • P

      Pontificia Universidad Católica de Chile

      Magíster en Salud Pública Global

      Skills you'll gain: Epidemiology, Public Health and Disease Prevention, Descriptive Analytics, Biostatistics, Statistical Reporting, Gerontology, Cloud Security, Healthcare Ethics, Digital Transformation, Sampling (Statistics), Assertiveness, Telehealth, Health Disparities, Health Administration, Public Health, Object Oriented Programming (OOP), Policy Analysis, Research Reports, Health Systems, Occupational Safety and Health Administration (OSHA)

      Earn a degree

      Degree · 1 - 4 Years

    • U

      University of Illinois at Urbana-Champaign

      Managerial Economics & Business Analysis Graduate Certificate

      Skills you'll gain: Data Storytelling, Management Accounting, Fund Accounting, Operations Management, Mergers & Acquisitions, Financial Statement Analysis, Marketing, Risk Management, Machine Learning Algorithms, Business Strategy, Financial Auditing, Descriptive Statistics, Variance Analysis, Process Improvement, Marketing Analytics, Generative AI, Financial Market, Strategic Decision-Making, Corporate Tax, Global Marketing

      Credit offered

      Graduate Certificate · 6 - 12 Months

    • U

      University of Illinois at Urbana-Champaign

      Global Challenges in Business Graduate Certificate

      Skills you'll gain: Data Storytelling, Management Accounting, Fund Accounting, Operations Management, Mergers & Acquisitions, Financial Statement Analysis, Marketing, Risk Management, Machine Learning Algorithms, Business Strategy, Financial Auditing, Descriptive Statistics, Variance Analysis, Process Improvement, Marketing Analytics, Generative AI, Financial Market, Strategic Decision-Making, Corporate Tax, Global Marketing

      Credit offered

      Graduate Certificate · 6 - 12 Months

    • O

      O.P. Jindal Global University

      M.A. Public Policy

      Skills you'll gain: Econometrics, Surveys, Environmental Laws, Sampling (Statistics), Social Sciences, Public Policies, Political Sciences, Data Collection, Health Disparities, Economics, Policy, and Social Studies, Economic Development, Policy Analysis, Presentations, International Relations, Diplomacy, Economics, Complex Problem Solving, Research Methodologies, Socioeconomics, Governance

      Earn a degree

      Degree · 1 - 4 Years

    • Status: New
      New
      G

      Google Cloud

      Usar o BigQuery ML para inferência

      Skills you'll gain: Analytics, Data Analysis, Big Data, Applied Machine Learning, Statistical Inference, Google Cloud Platform, Machine Learning Methods, SQL

      Beginner · Course · 1 - 4 Weeks

    • U

      Universidad de los Andes

      Maestría en Inteligencia Artificial

      Skills you'll gain: Real-Time Operating Systems, Supervised Learning, Unsupervised Learning, Reinforcement Learning, Cloud-Native Computing, Computer Vision, MLOps (Machine Learning Operations), Containerization, Natural Language Processing, Artificial Intelligence, Generative AI, Linear Algebra, Dimensionality Reduction, Probability & Statistics, Data Ethics, Machine Learning Methods, Control Systems, Epidemiology, Technical Communication, Bioinformatics

      Earn a degree

      Degree · 1 - 4 Years

    Searches related to bayesian statistics

    bayesian statistics: from concept to data analysis
    bayesian statistics: techniques and models
    bayesian statistics: time series analysis
    bayesian statistics: mixture models
    bayesian statistics: capstone project
    bayesian computational statistics
    introduction to bayesian statistics for data science
    1…104105106107

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

    • Master of Science in Machine Learning and Data Science: Imperial College London
    • Master of Applied Data Science: University of Michigan
    • Exploratory Data Analysis and Visualization: Microsoft
    • Data Science Graduate Certificate: University of Colorado Boulder
    • MBA Business Analytics: O.P. Jindal Global University
    • Magíster en Business Analytics: Pontificia Universidad Católica de Chile
    • Magíster en Salud Pública Global: Pontificia Universidad Católica de Chile
    • Managerial Economics & Business Analysis Graduate Certificate: University of Illinois at Urbana-Champaign
    • Global Challenges in Business Graduate Certificate: University of Illinois at Urbana-Champaign
    • M.A. Public Policy: O.P. Jindal Global University

    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 Bayesian Statistics

    Bayesian Statistics is an approach to statistics based on the work of the 18th century statistician and philosopher Thomas Bayes, and it is characterized by a rigorous mathematical attempt to quantify uncertainty. The likelihood of uncertain events is unknowable, by definition, but Bayes’s Theorem provides equations for the statistical inference of their probability based on prior information about an event - which can be updated based on the results of new data.

    While its origins lie hundreds of years in the past, Bayesian statistical approaches have become increasingly important in recent decades. The calculations at the heart of Bayesian statistics require intensive numerical integrations to solve, which were often infeasible before low-cost computing power became more widely accessible. But today, statisticians can evaluate integrals by running hundreds of thousands of simulation iterations with Markov chain Monte Carlo methods on an ordinary laptop computer.

    This new accessibility of computational power to quantify uncertainty has enabled Bayesian statistics to showcase its strength: making predictions. This capability is critical to many data science applications, and especially to the training of machine learning algorithms to create predictive analytics that assist with real-world decision-making problems. As with other areas of data science, statisticians often rely on R programming and Python programming skills to solve Bayesian equations.‎

    Bayesian statistical approaches are essential to many data science and machine learning techniques, making an understanding of Bayes’ Theorem and related concepts essential to careers in these fields.

    If you wish to dive more deeply into the theoretical aspects of Bayesian statistics and the modeling of probability more generally, you can also pursue a career as a statistician. These experts may work in academia or the private sector, and usually have at least a master’s degree in mathematics or statistics. According to the Bureau of Labor Statistics, statisticians earn a median annual salary of $91,160.‎

    Absolutely. Coursera gives you opportunities to learn about Bayesian statistics and related concepts in data science and machine learning through courses and Specializations from top-ranked schools like Duke University, the University of California, Santa Cruz, and the National Research University Higher School of Economics in Russia. You can also learn from industry leaders like Google Cloud, or through Coursera’s own exclusive Guided Projects, which let you build skills by completing step-by-step tutorials taught by expert instructors.

    Regardless of your needs, the combination of high-equality education, a flexible schedule, and low tuition costs leaves no uncertainty about the value of learning about Bayesian statistics on Coursera.‎

    A background in statistics and certain areas of math, like algebra, can be extremely helpful when learning Bayesian statistics. This includes knowledge of and experience with statistical methods and statistical software. Any type of experience working with data, especially on a large scale, can also help. Classes, degrees, or work experience in biostatistics, psychometrics, analytics, quantitative psychology, banking, and public health can also be beneficial, especially if you plan to enter a career that centers around one of these topics or a related field. However, they aren't necessary for learning about Bayesian statistics in general.‎

    People who aspire to work in roles that use Bayesian statistics should have analytical minds and a passion for using data to help other businesses and other people. You'll need good computer skills and a passion for statistics. You'll also need to be a good multitasker with excellent time management skills as well as someone who is highly organized. Good problem-solving skills are a must, as is flexibility. There are times when you may have total autonomy over your job and others when you're working with a team. That means you'll also need great interpersonal skills and the ability to communicate well, both verbally and in writing.‎

    Anyone who works with data or seeks a career working with data may be interested in learning Bayesian statistics. Many companies that seek employees to work in fields involving statistics or big data prefer someone who understands and can implement the theories of Bayesian statistics to someone who can't. These companies typically offer competitive salaries and benefits and room for career advancement. Careers that may use Bayesian statistics also tend to have a good outlook for the future. Best of all, learning about this topic can open you up to jobs in numerous industries, ranging from banking and finance to health care and biostatistics.‎

    Online Bayesian Statistics courses offer a convenient and flexible way to enhance your existing knowledge or learn new Bayesian Statistics skills. With a wide range of Bayesian Statistics classes, you can conveniently learn at your own pace to advance your Bayesian Statistics career skills.‎

    When looking to enhance your workforce's skills in Bayesian Statistics, 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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