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    Results for "advanced statistics"

    • Status: Free Trial
      Free Trial

      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, SQL, Data Visualization Software, Data Literacy, Data Collection, Sampling (Statistics), Data Analysis, Google Analytics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      314 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial

      University of Minnesota

      Analytics for Decision Making

      Skills you'll gain: Time Series Analysis and Forecasting, Simulations, Operations Research, Probability Distribution, Mathematical Modeling, Supply Chain, Probability, Predictive Modeling, Business Modeling, Business Analytics, Analytics, Regression Analysis, Microsoft Excel, Forecasting, Data Modeling, Process Optimization, Data-Driven Decision-Making, Statistics, Business Mathematics, Manufacturing Operations

      4.7
      Rating, 4.7 out of 5 stars
      ·
      260 reviews

      Beginner · Specialization · 3 - 6 Months

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      Free Trial

      University of Colorado Boulder

      Dynamic Programming, Greedy Algorithms

      Skills you'll gain: Theoretical Computer Science, Algorithms, Data Structures, Computational Thinking, Computer Programming, Computational Logic, Computer Science, Advanced Mathematics, Mathematical Theory & Analysis, Program Development, Analysis, Design Strategies, Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      221 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      Imperial College London

      Linear Regression in R for Public Health

      Skills you'll gain: Correlation Analysis, Regression Analysis, Data Analysis, R Programming, Descriptive Statistics, Statistical Modeling, Exploratory Data Analysis, Statistical Analysis, Statistical Programming, Statistical Software, Statistical Methods, Probability & Statistics, Biostatistics, Epidemiology, Data Import/Export

      4.8
      Rating, 4.8 out of 5 stars
      ·
      520 reviews

      Intermediate · Course · 1 - 4 Weeks

    • EDUCBA

      VFX with Adobe After Effects from Novice to Expert

      Skills you'll gain: Adobe After Effects, Motion Graphics, Animations, Post-Production, Computer Graphic Techniques, Video Editing, Timelines, 3D Modeling, Color Theory, Typography, Design Elements And Principles

      4.7
      Rating, 4.7 out of 5 stars
      ·
      140 reviews

      Beginner · Course · 1 - 3 Months

    • University of Colorado Boulder

      Introduction to High-Performance and Parallel Computing

      Skills you'll gain: Bash (Scripting Language), Scalability, Distributed Computing, Big Data, Operating Systems, File Systems, Linux, Job Control Language (JCL), Command-Line Interface, Performance Tuning, Computer Architecture

      Build toward a degree

      3.6
      Rating, 3.6 out of 5 stars
      ·
      138 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      DeepLearning.AI

      Generative Deep Learning with TensorFlow

      Skills you'll gain: Generative AI, Tensorflow, Image Analysis, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Computer Graphics, Unsupervised Learning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      306 reviews

      Intermediate · Course · 1 - 4 Weeks

    • University of Cape Town

      Doing Clinical Research: Biostatistics with the Wolfram Language

      Skills you'll gain: Descriptive Statistics, Data Literacy, Exploratory Data Analysis, Plot (Graphics), Statistical Analysis, Statistical Visualization, Statistical Programming, Biostatistics, Statistical Hypothesis Testing, Quantitative Research, Probability & Statistics, Deep Learning, Data Manipulation, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      50 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      University of Washington

      Machine Learning: Clustering & Retrieval

      Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Big Data, Statistical Inference, Text Mining, Statistical Modeling, Machine Learning Algorithms, Unstructured Data, Machine Learning, Sampling (Statistics), Scalability, Probability Distribution, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      University of California, Davis

      SQL for Data Science Capstone Project

      Skills you'll gain: Presentations, SQL, Descriptive Statistics, Data Storytelling, Data Analysis, Peer Review, Exploratory Data Analysis, Statistical Analysis, Data Modeling, Performance Metric, Analytical Skills, Business Analytics, Text Mining, Data Science, Data Import/Export, Target Audience, Data Manipulation, Proposal Development

      4.2
      Rating, 4.2 out of 5 stars
      ·
      236 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      ISC2

      Incident Response, BC, and DR Concepts

      Skills you'll gain: Incident Response, Business Continuity, Disaster Recovery, Cybersecurity, Security Management, Crisis Management, Information Assurance

      4.7
      Rating, 4.7 out of 5 stars
      ·
      241 reviews

      Beginner · Course · 1 - 3 Months

    • University of Alberta

      Science Literacy

      Skills you'll gain: Scientific Methods, General Science and Research, Research Methodologies, Research, Research Design, Peer Review, Experimentation, Statistical Methods, Media and Communications, Correlation Analysis, Probability & Statistics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      263 reviews

      Beginner · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…505152…269

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

    • Google Data Analytics: Google
    • Analytics for Decision Making: University of Minnesota
    • Dynamic Programming, Greedy Algorithms: University of Colorado Boulder
    • Linear Regression in R for Public Health : Imperial College London
    • VFX with Adobe After Effects from Novice to Expert: EDUCBA
    • Introduction to High-Performance and Parallel Computing: University of Colorado Boulder
    • Generative Deep Learning with TensorFlow: DeepLearning.AI
    • Doing Clinical Research: Biostatistics with the Wolfram Language: University of Cape Town
    • Machine Learning: Clustering & Retrieval: University of Washington
    • SQL for Data Science Capstone Project: University of California, Davis

    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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