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    Results for "advanced statistics"

    • Status: Free Trial
      Free Trial

      Fundação Instituto de Administração

      Data & Finance for the future

      Skills you'll gain: Financial Statement Analysis, Financial Statements, Financial Analysis, Business Analytics, Regression Analysis, Business Valuation, Descriptive Statistics, Data Analysis, Data-Driven Decision-Making, Statistical Inference, Financial Accounting, Cash Flows, Balance Sheet, Income Statement, Competitive Analysis, International Finance, Business Economics, Economics, Market Dynamics, Business Planning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      451 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial

      University of Virginia

      Product Analytics and AI

      Skills you'll gain: Customer Analysis, Analytics, Business Analytics, Usability Testing, Product Management, Customer Insights, A/B Testing, Product Development, Agile Methodology, User Experience, Advanced Analytics, Data-Driven Decision-Making, Data Science, Product Testing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      482 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      ESSEC Business School

      Foundations of strategic business analytics

      Skills you'll gain: Business Analytics, Forecasting, Data Presentation, Predictive Analytics, R Programming, Information Technology, Statistical Analysis, Communication, Business Strategy, Business, Statistics, Data Analysis, Data Visualization, Regression Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      655 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      IBM

      Supervised Machine Learning: Classification

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Applied Machine Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Data Processing, Data Cleansing, Machine Learning, Regression Analysis, Data Manipulation, Business Analytics, Feature Engineering, Random Forest Algorithm, Statistical Modeling, Sampling (Statistics), Performance Metric

      4.8
      Rating, 4.8 out of 5 stars
      ·
      411 reviews

      Intermediate · Course · 1 - 3 Months

    • National Taiwan University

      機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

      Skills you'll gain: Supervised Learning, Machine Learning, Classification And Regression Tree (CART), Theoretical Computer Science, Applied Mathematics, Mathematical Modeling, Probability & Statistics, Regression Analysis, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      932 reviews

      Beginner · Course · 1 - 3 Months

    • Pontificia Universidad Católica de Chile

      Introducción a la Minería de Datos

      Skills you'll gain: Exploratory Data Analysis, Data Mining, Data Analysis, Machine Learning Algorithms, Data Manipulation, Databases, Data Science, Machine Learning Methods, Unsupervised Learning, Supervised Learning, Classification And Regression Tree (CART), Algorithms, Performance Testing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.3K reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial

      DeepLearning.AI

      Data Analytics Foundations

      Skills you'll gain: Data Storytelling, Google Sheets, Data Visualization, Spreadsheet Software, Large Language Modeling, Data Literacy, Data Presentation, Data Visualization Software, Business Analysis, Data Analysis, Analytics, Business Requirements, Exploratory Data Analysis, Data-Driven Decision-Making, Stakeholder Engagement

      4.7
      Rating, 4.7 out of 5 stars
      ·
      79 reviews

      Beginner · Course · 1 - 4 Weeks

    • The Hong Kong University of Science and Technology

      Fibonacci Numbers and the Golden Ratio

      Skills you'll gain: Arithmetic, Geometry, Mathematical Theory & Analysis, Advanced Mathematics, Combinatorics, Algebra, Mathematical Modeling, Applied Mathematics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      SAS

      Doing More with SAS Programming

      Skills you'll gain: SAS (Software), Data Manipulation, Consolidation, Data Transformation, Data Processing, Data Analysis, Data Presentation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      939 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      University of Toronto

      Visual Perception for Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Computer Graphics, Artificial Neural Networks, Visualization (Computer Graphics), Artificial Intelligence and Machine Learning (AI/ML), Python Programming, Linear Algebra

      4.7
      Rating, 4.7 out of 5 stars
      ·
      581 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      Rice University

      Introduction to Biology: Ecology, Evolution, & Biodiversity

      Skills you'll gain: Biology, Environment, Microbiology, Life Sciences, Environmental Science, Environmental Issue, Environment and Resource Management, Demography, Natural Resource Management, Anatomy, Molecular Biology, Taxonomy, Estimation, Scientific Methods, Research, Experimentation, Data Collection, Research Methodologies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      211 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial

      The Hong Kong University of Science and Technology

      Vector Calculus for Engineers

      Skills you'll gain: Integral Calculus, Engineering Calculations, Calculus, Engineering Analysis, Engineering, Geometry, Advanced Mathematics, Mechanical Engineering, Applied Mathematics, Electrical Engineering, Physics, Derivatives

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…394041…268

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

    • Data & Finance for the future: Fundação Instituto de Administração
    • Product Analytics and AI: University of Virginia
    • Foundations of strategic business analytics: ESSEC Business School
    • Supervised Machine Learning: Classification: IBM
    • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
    • Introducción a la Minería de Datos: Pontificia Universidad Católica de Chile
    • Data Analytics Foundations: DeepLearning.AI
    • Fibonacci Numbers and the Golden Ratio: The Hong Kong University of Science and Technology
    • Doing More with SAS Programming: SAS
    • Visual Perception for 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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