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    Results for "advanced statistics"

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      University of Illinois Urbana-Champaign

      Business Data Management and Communication

      Skills you'll gain: Data Storytelling, Revenue Recognition, Financial Statements, Data Presentation, Data Visualization, Accrual Accounting, Cash Flows, Financial Accounting, Data Collection, Financial Statement Analysis, Bookkeeping, Income Statement, Data Visualization Software, Business Valuation, Tidyverse (R Package), Data Quality, Data Processing, Business Analytics, Asset Management, Analytics

      4.7
      Rating, 4.7 out of 5 stars
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      6.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • C

      Coursera Instructor Network

      Active Listening: Enhancing Communication Skills

      Skills you'll gain: Active Listening, Non-Verbal Communication, Cultural Diversity, Conflict Management, Emotional Intelligence, Empathy, Interpersonal Communications, Leadership, Rapport Building, Collaboration, Communication, Self-Awareness, Adaptability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      475 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Six Sigma Green Belt

      Skills you'll gain: Statistical Process Controls, Statistical Hypothesis Testing, Process Capability, Team Management, Quality Improvement, Root Cause Analysis, Six Sigma Methodology, Lean Six Sigma, Lean Methodologies, Exploratory Data Analysis, Process Improvement, Quality Control, Probability & Statistics, Operational Excellence, Statistical Analysis, Process Analysis, Process Mapping, Correlation Analysis, Business Process Management, Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
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      4.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Capstone: Retrieving, Processing, and Visualizing Data with Python

      Skills you'll gain: Data Processing, Data Collection, Data Visualization Software, Data Manipulation, Python Programming, Exploratory Data Analysis, Algorithms, Data Analysis, Web Scraping, Unstructured Data

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Six Sigma Yellow Belt

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Lean Methodologies, Data Collection, Process Improvement, Quality Improvement, Process Optimization, Lean Six Sigma, Correlation Analysis, Statistical Hypothesis Testing, Kaizen Methodology, Process Analysis, Probability Distribution, Regression Analysis, Process Capability, Business Process, Statistical Process Controls, Quality Management, Team Management, Continuous Improvement Process

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Beginner · Specialization · 3 - 6 Months

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      Free Trial
      U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

      4.7
      Rating, 4.7 out of 5 stars
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      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

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      Google

      Foundations of Data Science

      Skills you'll gain: Data Storytelling, Data Ethics, Data Analysis, Workflow Management, Data-Driven Decision-Making, Analytical Skills, Data Science, Project Design, Communication, Business, Business Workflow Analysis, Stakeholder Communications, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.2K reviews

      Advanced · Course · 1 - 3 Months

    • L

      LearnQuest

      Advanced Java

      Skills you'll gain: Apache Maven, Spring Framework, Microservices, Spring Boot, Java, Back-End Web Development, Software Architecture, Server Side, Load Balancing, Cloud Development, Restful API, Systems Architecture, Web Applications, Scalability

      4.4
      Rating, 4.4 out of 5 stars
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      48 reviews

      Advanced · Course · 1 - 4 Weeks

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      DeepLearning.AI

      Natural Language Processing with Classification and Vector Spaces

      Skills you'll gain: Natural Language Processing, Supervised Learning, Dimensionality Reduction, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Tensorflow, Linear Algebra, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
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      4.6K reviews

      Intermediate · Course · 1 - 4 Weeks

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      University of Toronto

      Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Control Systems, Embedded Software, Automation, Deep Learning, Simulation and Simulation Software, Software Architecture, Computer Graphics, Safety Assurance, Artificial Neural Networks, Global Positioning Systems, Visualization (Computer Graphics), Estimation, Algorithms, Machine Learning Methods, Predictive Modeling, Scenario Testing, Data Structures, Spatial Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
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      3.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • T

      The University of North Carolina at Chapel Hill

      Epidemiology: The Basic Science of Public Health

      Skills you'll gain: Epidemiology, Public Health and Disease Prevention, Public Health, Infectious Diseases, Research Design, Health Policy, Biostatistics, Science and Research, Health Care, Probability & Statistics, Statistical Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.9K reviews

      Mixed · Course · 1 - 3 Months

    • T

      The University of Sydney

      Introduction to Calculus

      Skills you'll gain: Calculus, Integral Calculus, Algebra, Advanced Mathematics, Geometry, Applied Mathematics, Engineering Calculations, Trigonometry, Arithmetic, Derivatives, Mathematical Modeling, Graphing, Estimation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.8K reviews

      Intermediate · 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

    • Business Data Management and Communication: University of Illinois Urbana-Champaign
    • Active Listening: Enhancing Communication Skills: Coursera Instructor Network
    • Six Sigma Green Belt: Kennesaw State University
    • Capstone: Retrieving, Processing, and Visualizing Data with Python: University of Michigan
    • Six Sigma Yellow Belt: Kennesaw State University
    • Reinforcement Learning: University of Alberta
    • Foundations of Data Science: Google
    • Advanced Java: LearnQuest
    • Natural Language Processing with Classification and Vector Spaces: DeepLearning.AI
    • Self-Driving Cars: University of Toronto

    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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