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    Results for "advanced statistics"

    • Status: Free Trial
      Free Trial
      N

      Northwestern University

      Modern Robotics, Course 1: Foundations of Robot Motion

      Skills you'll gain: Engineering, Mechanics, Mathematical Modeling, Torque (Physics), Simulation and Simulation Software, Matlab, Linear Algebra, Angular

      4.7
      Rating, 4.7 out of 5 stars
      ·
      991 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      A Crash Course in Causality: Inferring Causal Effects from Observational Data

      Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Statistical Software, Statistical Modeling, Statistical Inference, Data Analysis, Probability & Statistics, Regression Analysis, Research Design, Graph Theory

      4.7
      Rating, 4.7 out of 5 stars
      ·
      564 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Foundations of Public Health Practice

      Skills you'll gain: Public Health, Health Equity, Health Disparities, Microbiology, Health Assessment, Sanitation, Program Evaluation, Epidemiology, Infectious Diseases, Health Policy, Preventative Care, Behavioral Economics, Community Health, Data Literacy, Behavioral Health, Intelligence Collection and Analysis, Emergency Response, Health And Safety Standards, Public Health and Disease Prevention, Health Systems

      4.8
      Rating, 4.8 out of 5 stars
      ·
      636 reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      Duke University

      Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital

      Skills you'll gain: Image Analysis, Computer Vision, Digital Communications, Computer Graphics, Visualization (Computer Graphics), Medical Imaging, Applied Mathematics, Spatial Analysis, Advanced Mathematics, Linear Algebra, Matlab, Mathematical Modeling, Algorithms, Probability Distribution

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.1K reviews

      Mixed · Course · 1 - 3 Months

    • S

      Stanford University

      Game Theory II: Advanced Applications

      Skills you'll gain: Game Theory, Bidding, Social Sciences, Resource Allocation, Political Sciences, Economics, Behavioral Economics, Negotiation, Mathematical Theory & Analysis, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      642 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft AI & ML Engineering

      Skills you'll gain: Unsupervised Learning, Generative AI, Large Language Modeling, Data Management, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure Architecture, Cloud Infrastructure, Generative AI Agents, Applied Machine Learning, Reinforcement Learning, Data Ethics, Prompt Engineering, Data Processing, Artificial Intelligence, Application Deployment

      4.6
      Rating, 4.6 out of 5 stars
      ·
      147 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      The Nuts and Bolts of Machine Learning

      Skills you'll gain: Feature Engineering, Statistical Machine Learning, Advanced Analytics, Predictive Modeling, Unsupervised Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Data Analysis, Performance Tuning, Python Programming

      4.8
      Rating, 4.8 out of 5 stars
      ·
      517 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      Q

      Queen Mary University of London

      Market Research

      Skills you'll gain: Qualitative Research, Proposal Development, Market Research, Research Reports, Data Collection, Research Design, Research Methodologies, Data Analysis, Statistical Hypothesis Testing, Survey Creation, Statistical Analysis, Surveys, Correlation Analysis, Quantitative Research, Research, Science and Research, Market Analysis, Focus Group, Regression Analysis, Content Performance Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      462 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      N

      New York University

      Machine Learning and Reinforcement Learning in Finance

      Skills you'll gain: Supervised Learning, Reinforcement Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Artificial Neural Networks, Decision Tree Learning, Predictive Modeling, Financial Trading, Financial Market, Derivatives, Scikit Learn (Machine Learning Library), Markov Model, Regression Analysis, Deep Learning, Market Liquidity, Financial Services

      3.7
      Rating, 3.7 out of 5 stars
      ·
      814 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      The Structured Query Language (SQL)

      Skills you'll gain: SQL, Database Systems, Database Theory, Database Management, Query Languages, Database Design, Relational Databases, Data Access, Data Analysis, Data Manipulation, Data Modeling, Data Integrity

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Managing Data Analysis

      Skills you'll gain: Exploratory Data Analysis, Data Presentation, Data Analysis, Data Management, Management Training And Development, Technical Communication, Team Management, Analytical Skills, Team Leadership, Statistical Inference, Statistical Modeling, Communication

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      M

      Macquarie University

      Excel Power Tools for Data Analysis

      Skills you'll gain: Power BI, Data Analysis Expressions (DAX), Data Visualization Software, Data Modeling, Microsoft Excel, Interactive Data Visualization, Pivot Tables And Charts, Data Transformation, Dashboard, Data Manipulation, Data Analysis Software, Microsoft Power Platform, Data Import/Export, Data Cleansing

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to advanced statistics

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

    • Modern Robotics, Course 1: Foundations of Robot Motion: Northwestern University
    • A Crash Course in Causality: Inferring Causal Effects from Observational Data: University of Pennsylvania
    • Foundations of Public Health Practice: Imperial College London
    • Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital: Duke University
    • Game Theory II: Advanced Applications: Stanford University
    • Microsoft AI & ML Engineering: Microsoft
    • The Nuts and Bolts of Machine Learning: Google
    • Market Research: Queen Mary University of London
    • Machine Learning and Reinforcement Learning in Finance: New York University
    • The Structured Query Language (SQL): University of Colorado Boulder

    Frequently Asked Questions about Advanced Statistics

    Advanced statistics are the mathematical tools used to discover and explore complex relationships between different variables in large datasets. In contrast to basic statistics such as average and analysis of variance (ANOVA) that simply describe the characteristics of a dataset, advanced statistical approaches often seek to make predictions about the world. This requires the use of more sophisticated statistical inference tools, such as generalized linear models for regression analysis capable of establishing how multiple interrelated factors may impact projected outcomes.

    These advanced statistical methods are increasingly important in the field of data science, which is tasked with uncovering important business insights and developing predictive models from diverse big data-scale datasets. These techniques are also especially important for the proper training and use of machine learning algorithms. As in data science and machine learning more generally, R programming and Python programming skills are typically relied upon to conduct these advanced statistical analyses.‎

    Advanced statistics skills are essential for work in data science, machine learning, and artificial intelligence (AI), as statistical approaches are at the heart of the learning algorithms that make these applications possible. An understanding of statistics is likewise important for professionals in finance, healthcare, and other industries that are increasingly making use of machine learning and AI, as they increasingly need to work closely with data scientists to ensure that these powerful techniques are developed to solve the right business problems.

    Those wishing to delve deeper into advanced statistical methods and help develop new mathematical approaches in the field may pursue a master’s or even a PhD in statistics. These experts work in academia, government, or at private sector companies involved in scientific or engineering research. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160, and this specialized career path is expected to be in high demand due to expanding opportunities to use statistics to navigate our data-rich world.‎

    Certainly. Coursera offers a variety of courses in advanced statistics as well as their applications in the context of fields like data science and machine learning. In fact, coursework in statistics is often a prerequisite for data science classes. Regardless of your level of expertise and needs in these areas, Coursera enables you to learn remotely from top-ranked schools like the University of Michigan, Johns Hopkins University, and Duke University. And, since you can view course materials and complete coursework on a flexible schedule, there’s an exceedingly high probability that you can fit online learning about advanced statistics into your existing school or work life.‎

    You need to have strong math skills, especially in basic calculus, linear algebra, and statistics before starting to learn advanced statistics. It's important that you have strong technical skills and are very comfortable on the computer, strong analytical skills, and the ability to carefully examine and question data that is presented to you so that you can organize and draw conclusions from it. For learning some concepts in advanced statistics, you'll need to have experience using the R statistical software package and understand Bayesian estimation, principles of maximum-likelihood estimation, and calculus-based probability.‎

    People who enjoy mathematics are best suited for roles in advanced statistics, especially those who enjoy concepts like probability, linear models, and statistics and how they relate to data science. They can quickly grasp and apply complex technical concepts as well. Those who enjoy testing hypotheses and figuring out uncertain outcomes based on probability are also well suited for roles in advanced statistics. Also, people who have wide-ranging computer skills, the ability to communicate their statistical findings in plain language, problem-solving and analytical skills, and teamwork and collaborative skills are best suited for roles involving advanced statistics.‎

    If you're aspiring to be a biostatistician or data scientist, learning advanced statistics is probably right for you. If you're interested in machine learning and the development of data products, you may also find learning advanced statistics is right for you. People who want to have a career as a statistician, statistical epidemiologist, sports analyst, actuary, market researcher, or investment analyst may also find learning advanced statistics to be the right choice. And if you need to understand how to transform complex sets of data into practical applications, learning advanced statistics is right for you.‎

    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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