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    • Advanced Statistics

    篩選依據

    ''advanced statistics'的 266 個結果

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      Johns Hopkins University

      Advanced Statistics for Data Science

      您將獲得的技能: Algebra, Artificial Neural Networks, Bayesian Statistics, Biostatistics, Calculus, Communication, Dimensionality Reduction, Econometrics, Experiment, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematics, Probability & Statistics, Probability Distribution, Regression, Statistical Machine Learning, Statistical Tests

      4.4

      (660 條評論)

      Advanced · Specialization · 3-6 Months

    • 免費

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      Georgia Institute of Technology

      Materials Data Sciences and Informatics

      您將獲得的技能: Design and Product, User Experience, Probability & Statistics, Experiment, Data Analysis, Data Management, Machine Learning, Materials, Computer Programming, Dimensionality Reduction, Computer Programming Tools, Human Computer Interaction, Big Data, General Statistics

      4.5

      (296 條評論)

      Intermediate · Course · 1-3 Months

    • 免費

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      Nanjing University

      Data Processing Using Python

      您將獲得的技能: Python Programming, Computer Programming, Statistical Programming

      4.1

      (277 條評論)

      Beginner · Course · 1-3 Months

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      University of Colorado Boulder

      Business Analytics for Decision Making

      您將獲得的技能: Data Clustering Algorithms, Analytics, Theoretical Computer Science, Business Analysis, Mathematical Theory & Analysis, Machine Learning Algorithms, Data Analysis, Markov Model, Business Analytics, Machine Learning, Mathematical Optimization, Big Data, Analysis, Simulation, Algorithms

      4.6

      (1.7k 條評論)

      Mixed · Course · 1-4 Weeks

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      Coursera Project Network

      Analyze Survey Data with Tableau

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Create a Custom Marketing Analytics Dashboard in Data Studio

      您將獲得的技能: Analysis, Data Analysis, Marketing, Market (Economics), Data Visualization

      4.4

      (61 條評論)

      Intermediate · Guided Project · Less Than 2 Hours

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      Johns Hopkins University

      Data Science: Foundations using R

      您將獲得的技能: Analysis, Application Development, Business Analysis, Computer Programming, Data Analysis, Data Management, Data Visualization, Exploratory Data Analysis, Extract, Transform, Load, Ggplot2, Knitr, Plot (Graphics), Probability & Statistics, R Programming, Software, Software Engineering Tools, Statistical Programming

      4.6

      (46.6k 條評論)

      Beginner · Specialization · 3-6 Months

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      DeepLearning.AI

      Advanced Learning Algorithms

      您將獲得的技能: Probability Distribution, Mathematics, Probability & Statistics, Data Structures, Theoretical Computer Science, Machine Learning Algorithms, Computer Programming, Data Management, Machine Learning, Artificial Neural Networks, Python Programming, Deep Learning, Tensorflow, Statistical Programming, Linear Algebra, Applied Machine Learning, Statistical Machine Learning, Computer Vision, General Statistics, Decision Tree

      4.9

      (382 條評論)

      Beginner · Course · 1-4 Weeks

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      免費

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      Stanford University

      Introduction to Statistics

      您將獲得的技能: Econometrics, Basic Descriptive Statistics, Statistical Tests, Experiment, Bayesian Statistics, Probability Distribution, Plot (Graphics), Regression, Probability & Statistics, Data Analysis, Probability, Machine Learning, Data Visualization, Statistical Analysis, General Statistics, Correlation And Dependence, Statistical Hypothesis Testing, Statistical Inference, Markov Model, Inference, Hypothesis Testing

      4.5

      (1.3k 條評論)

      Beginner · Course · 1-3 Months

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      University of Michigan

      Statistics with Python

      您將獲得的技能: Analysis, Basic Descriptive Statistics, Bayesian Statistics, Business Analysis, Computer Programming, Correlation And Dependence, Data Analysis, Data Visualization, Econometrics, Experiment, General Statistics, Inference, Machine Learning, Machine Learning Algorithms, Plot (Graphics), Probability & Statistics, Programming Principles, Python Programming, Regression, Statistical Analysis, Statistical Inference, Statistical Programming, Statistical Tests, Statistical Visualization

      4.6

      (2.8k 條評論)

      Beginner · Specialization · 1-3 Months

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      IBM Skills Network

      Advanced Data Science with IBM

      您將獲得的技能: Algorithms, Apache, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Bayesian Statistics, Big Data, Change Management, Cloud Computing, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Management, Data Model, Data Structures, Data Visualization, Databases, Deep Learning, Dimensionality Reduction, Distributed Computing Architecture, Econometrics, Estimation, Experiment, Extract, Transform, Load, General Statistics, IBM Cloud, Leadership and Management, Machine Learning, Machine Learning Algorithms, Natural Language Processing, Plot (Graphics), Probability & Statistics, Probability Distribution, Programming Principles, Python Programming, Regression, SQL, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Strategy and Operations, Tensorflow, Theoretical Computer Science

      4.3

      (2.9k 條評論)

      Advanced · Specialization · 3-6 Months

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      Johns Hopkins University

      Data Science: Statistics and Machine Learning

      您將獲得的技能: Algorithms, Applied Machine Learning, Business Analysis, Data Analysis, Data Visualization, Econometrics, General Statistics, Interactive Data Visualization, Interactivity, Machine Learning, Machine Learning Algorithms, Natural Language, Natural Language Processing, Plot (Graphics), Probability, Probability & Statistics, Probability Distribution, R Programming, Regression, Statistical Analysis, Statistical Programming, Statistical Tests, Theoretical Computer Science

      4.4

      (7k 條評論)

      Intermediate · Specialization · 3-6 Months

    與 advanced statistics 相關的搜索

    advanced statistics for data science
    advanced linear models for data science 2: statistical linear models
    1234…23

    總之,這是我們最受歡迎的 advanced statistics 門課程中的 10 門

    • Advanced Statistics for Data Science: Johns Hopkins University
    • Materials Data Sciences and Informatics: Georgia Institute of Technology
    • Data Processing Using Python: Nanjing University
    • Business Analytics for Decision Making: University of Colorado Boulder
    • Analyze Survey Data with Tableau: Coursera Project Network
    • Create a Custom Marketing Analytics Dashboard in Data Studio: Coursera Project Network
    • Data Science: Foundations using R: Johns Hopkins University
    • Advanced Learning Algorithms: DeepLearning.AI
    • Introduction to Statistics: Stanford University
    • Statistics with Python: University of Michigan

    關於 高級統計 的常見問題

    • 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.‎

    此常見問題解答內容僅供參考。建議學生多做研究,確保所追求的課程和其他證書符合他們的個人、專業和財務目標。
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