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    Results for "advanced statistics"

    • P

      Palo Alto Networks

      Palo Alto Networks Cybersecurity Foundation

      Skills you'll gain: Cybersecurity, Zero Trust Network Access, Cyber Threat Intelligence, Malware Protection, Network Security, Firewall, Threat Detection, Cloud Security, Endpoint Security, Security Controls, Enterprise Security, Software As A Service, Cloud Computing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      489 reviews

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Computer Vision Fundamentals with Google Cloud

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Applied Machine Learning, Artificial Neural Networks, Deep Learning, Supervised Learning, Google Cloud Platform, Machine Learning Methods, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Small Data, Data Processing, Cloud API

      4.5
      Rating, 4.5 out of 5 stars
      ·
      543 reviews

      Advanced · Course · 1 - 3 Months

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      Microsoft

      Microsoft Generative AI for Data Analysis

      Skills you'll gain: Prompt Engineering, Data Storytelling, Data Presentation, Dashboard, Interactive Data Visualization, Generative AI, Data Ethics, Data Visualization, Infographics, Anomaly Detection, Excel Formulas, Predictive Modeling, Data Visualization Software, Microsoft Copilot, Business Reporting, Risk Analysis, Text Mining, Risk Management, Data Quality, Data Pipelines

      4.3
      Rating, 4.3 out of 5 stars
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      61 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • W

      Wesleyan University

      Data Management and Visualization

      Skills you'll gain: Descriptive Statistics, Data Manipulation, Data Presentation, Data Management, Data Literacy, Graphing, SAS (Software), Peer Review, Data Analysis, Statistics, Research Reports, Exploratory Data Analysis, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
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      937 reviews

      Mixed · Course · 1 - 3 Months

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      University of California, Irvine

      E-Marketing

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      4.7
      Rating, 4.7 out of 5 stars
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      385 reviews

      Beginner · Specialization · 1 - 3 Months

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      National Taiwan University

      3D CAD Application

      Skills you'll gain: SketchUp (3D Modeling Software), 3D Modeling, Construction, Building Design, Architectural Drawing, Architecture and Construction, Computer-Aided Design

      4.8
      Rating, 4.8 out of 5 stars
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      158 reviews

      Intermediate · Course · 1 - 3 Months

    • G

      Google

      Google Data Analytics

      Skills you'll gain: Data Presentation, Data Storytelling, Presentations, Data Cleansing, Data Visualization, Rmarkdown, Data-Driven Decision-Making, Data Validation, Data Ethics, Analytical Skills, Dashboard, Spreadsheet Software, Ggplot2, Google Sheets, SQL, Data Literacy, Data Collection, Sampling (Statistics), Data Analysis, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
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      312 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free
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      V

      Vanderbilt University

      Case Studies in Personalized Medicine

      Skills you'll gain: Precision Medicine, Medical Science and Research, Health Informatics, Biostatistics, Electronic Medical Record, Healthcare Ethics, General Medicine, Clinical Research, Probability & Statistics, Statistical Analysis, Molecular Biology, Pharmacology

      4.8
      Rating, 4.8 out of 5 stars
      ·
      496 reviews

      Mixed · Course · 1 - 3 Months

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      University of Pennsylvania

      Global Trends for Business and Society

      Skills you'll gain: Demography, Market Trend, Trend Analysis, International Relations, Socioeconomics, Social Sciences, Systems Thinking, Cultural Diversity, Financial Systems, World History, Economics, Business Economics, Governance

      4.8
      Rating, 4.8 out of 5 stars
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      919 reviews

      Mixed · Course · 1 - 4 Weeks

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      IBM

      IBM AI Enterprise Workflow

      Skills you'll gain: Feature Engineering, Data Ethics, Exploratory Data Analysis, Unsupervised Learning, Tensorflow, Application Deployment, Dimensionality Reduction, MLOps (Machine Learning Operations), Probability Distribution, Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Dashboard, Unit Testing, Docker (Software), Artificial Neural Networks, Data Science, Artificial Intelligence

      4.3
      Rating, 4.3 out of 5 stars
      ·
      319 reviews

      Advanced · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Data – What It Is, What We Can Do With It

      Skills you'll gain: Data Literacy, Data Analysis, Research Design, Descriptive Statistics, Analytics, Analysis, Statistics, Quantitative Research, Statistical Methods, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      172 reviews

      Beginner · Course · 1 - 4 Weeks

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      Yonsei University

      Deep Learning for Business

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      4.4
      Rating, 4.4 out of 5 stars
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      680 reviews

      Beginner · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
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    In summary, here are 10 of our most popular advanced statistics courses

    • Palo Alto Networks Cybersecurity Foundation: Palo Alto Networks
    • Computer Vision Fundamentals with Google Cloud: Google Cloud
    • Microsoft Generative AI for Data Analysis: Microsoft
    • Data Management and Visualization: Wesleyan University
    • E-Marketing: University of California, Irvine
    • 3D CAD Application: National Taiwan University
    • Google Data Analytics: Google
    • Case Studies in Personalized Medicine: Vanderbilt University
    • Global Trends for Business and Society: University of Pennsylvania
    • IBM AI Enterprise Workflow: IBM

    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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