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    Results for "advanced statistics"

    • J

      Johns Hopkins University

      Principles of fMRI 1

      Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Data Analysis, Research Design, Image Analysis, Neurology, Science and Research, Statistical Analysis, Statistical Modeling, Data Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      837 reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Natural Language Processing with Probabilistic Models

      Skills you'll gain: Natural Language Processing, Markov Model, Text Mining, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Machine Learning Methods, Data Processing, Algorithms, Data Cleansing, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 4 Weeks

    • S

      SAS

      Getting Started with SAS Programming

      Skills you'll gain: SAS (Software), Data Import/Export, Data Validation, Data Access, Data Manipulation, Exploratory Data Analysis, Data Analysis, SQL, Data Presentation, Microsoft Excel, Descriptive Statistics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.1K reviews

      Beginner · Course · 1 - 3 Months

    • U

      Universidad Austral

      Marketing Digital

      Skills you'll gain: Social Media, Social Media Strategy, Social Media Marketing, Google Ads, Digital Marketing, Customer Relationship Management, Media Buying, Digital Media Strategy, Marketing Analytics, Campaign Management, LinkedIn, Facebook, Web Analytics, Pay Per Click Advertising, Marketing Strategies, Marketing, Keyword Research, Paid media, Performance Analysis, Online Advertising

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      Duke University

      Mastering Data Analysis in Excel

      Skills you'll gain: Microsoft Excel, Probability Distribution, Business Risk Management, Predictive Modeling, Regression Analysis, Risk Modeling, Business Analytics, Statistical Methods, Forecasting, Data Analysis, Probability, Financial Modeling, Classification And Regression Tree (CART), Performance Metric

      4.2
      Rating, 4.2 out of 5 stars
      ·
      3.9K reviews

      Mixed · Course · 1 - 3 Months

    • Status: New
      New
      M

      Microsoft

      Microsoft Python Development

      Skills you'll gain: Web Scraping, Data Structures, Git (Version Control System), Generative AI, Version Control, Matplotlib, Plotly, DevOps, Agile Methodology, Web Development, Data Ethics, Flask (Web Framework), Scripting, GitHub, Debugging, Data Cleansing, Data Manipulation, Restful API, Docker (Software), Test Driven Development (TDD)

      4.3
      Rating, 4.3 out of 5 stars
      ·
      162 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Colorado Boulder

      Excel/VBA for Creative Problem Solving, Part 1

      Skills you'll gain: Excel Macros, Programming Principles, Visual Basic (Programming Language), Data Structures, Program Development, Computer Programming, Spreadsheet Software, Automation, Algorithms, Debugging, Data Management, Data Cleansing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.3K reviews

      Beginner · Course · 1 - 3 Months

    • N

      New York Institute of Finance

      Introduction to Risk Management

      Skills you'll gain: Risk Management, Business Risk Management, Risk Modeling, Operational Risk, Enterprise Risk Management (ERM), Credit Risk, Risk Analysis, Portfolio Management, Capital Markets, Financial Market, Financial Regulation, Financial Modeling, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      687 reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Hands-on Introduction to Linux Commands and Shell Scripting

      Skills you'll gain: Linux Commands, Bash (Scripting Language), Shell Script, File Management, Unix Shell, Linux, File Systems, Unix Commands, Linux Servers, Scripting, Command-Line Interface, Linux Administration, Scripting Languages, Unix, Operating Systems, Network Protocols, OS Process Management, TCP/IP, Network Administration, Automation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California, Irvine

      Advanced Writing

      Skills you'll gain: Writing, Grammar, Editing, Proofreading, Peer Review

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Michigan

      Fitting Statistical Models to Data with Python

      Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Analysis, Statistical Programming, Regression Analysis, Predictive Modeling, Jupyter, Exploratory Data Analysis, Statistical Hypothesis Testing, Correlation Analysis, Probability Distribution

      4.4
      Rating, 4.4 out of 5 stars
      ·
      699 reviews

      Intermediate · Course · 1 - 4 Weeks

    • B

      Board Infinity

      Java FullStack Developer

      Skills you'll gain: Angular, Web Applications, HTML and CSS, Web Development, Eclipse (Software), JavaScript Frameworks, Spring Boot, Object Oriented Programming (OOP), Restful API, Java Programming, Model View Controller, Object Oriented Design, Hypertext Markup Language (HTML), Front-End Web Development, Software Development Tools, Spring Framework, Java, Web Services, Javascript, Integrated Development Environments

      4.3
      Rating, 4.3 out of 5 stars
      ·
      641 reviews

      Intermediate · Specialization · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…252627…263

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

    • Principles of fMRI 1: Johns Hopkins University
    • Natural Language Processing with Probabilistic Models: DeepLearning.AI
    • Getting Started with SAS Programming: SAS
    • Marketing Digital: Universidad Austral
    • Mastering Data Analysis in Excel: Duke University
    • Microsoft Python Development: Microsoft
    • Excel/VBA for Creative Problem Solving, Part 1: University of Colorado Boulder
    • Introduction to Risk Management: New York Institute of Finance
    • Hands-on Introduction to Linux Commands and Shell Scripting: IBM
    • Advanced Writing: University of California, Irvine

    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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