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    • Statistics For Data Science

    篩選依據

    ''statistics for data science'的 1071 個結果

    • 免費

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      Stanford University

      Introduction to Statistics

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

      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, Linearity, Logistic Regression, Machine Learning, Machine Learning Algorithms, Modeling, Plot (Graphics), Probability & Statistics, Programming Principles, Python Programming, Regression, Statistical Analysis, 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

      Statistics for Data Science with Python

      您將獲得的技能: Statistical Tests, Business Analysis, Correlation And Dependence, Plot (Graphics), Statistical Analysis, Data Analysis, Data Visualization, Statistical Visualization, Probability Distribution, Basic Descriptive Statistics, General Statistics, Probability & Statistics, Regression

      4.6

      (218 條評論)

      Mixed · Course · 1-3 Months

    • 免費

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      Duke University

      Data Science Math Skills

      您將獲得的技能: Mathematical Theory & Analysis, Theoretical Computer Science, Plot (Graphics), Computational Logic, Algebra, Bayesian Statistics, Data Visualization, Bayesian, Probability Distribution, Mathematics, General Statistics, Graph Theory, Probability & Statistics, Probability

      4.5

      (10.4k 條評論)

      Beginner · Course · 1-3 Months

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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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      Eindhoven University of Technology

      Improving your statistical inferences

      您將獲得的技能: Statistical Tests, Data Analysis, Business Analysis, Euler'S Totient Function, Analysis, Statistical Analysis, General Statistics, Hypothesis, Bayesian Statistics, Statistical Hypothesis Testing, Machine Learning, Statistical Inference, Bayesian, Bayesian Network, Experiment, Inference, Probability & Statistics, Hypothesis Testing

      4.9

      (725 條評論)

      Intermediate · Course · 1-3 Months

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      Imperial College London

      Mathematics for Machine Learning

      您將獲得的技能: Algebra, Algorithms, Analysis, Artificial Neural Networks, Basic Descriptive Statistics, Calculus, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis, Deep Learning, Differential Equations, General Statistics, Lambda Calculus, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Matrices, Probability & Statistics, Probability Distribution, Python Programming, Regression, Statistical Programming, Theoretical Computer Science

      4.6

      (12.8k 條評論)

      Beginner · Specialization · 3-6 Months

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      IBM Skills Network

      Tools for Data Science

      您將獲得的技能: Python Programming, Rstudio, SPSS, Statistical Programming, Machine Learning, Computer Programming, R Programming

      4.5

      (24.4k 條評論)

      Beginner · Course · 1-4 Weeks

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      Duke University

      Data Analysis with R

      您將獲得的技能: Bayesian Statistics, Business Analysis, Data Analysis, Data Mining, Data Visualization, Econometrics, Experiment, Exploratory Data Analysis, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, Modeling, Plot (Graphics), Probability & Statistics, Probability Distribution, R Programming, Regression, Regression Analysis, Statistical Analysis, Statistical Inference, Statistical Programming, Statistical Tests

      4.7

      (6.6k 條評論)

      Beginner · Specialization · 3-6 Months

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      Google

      Google Data Analytics

      您將獲得的技能: Algorithms, Application Development, Bias, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Security, Data Structures, Data Type, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, General Statistics, Interactive Data Visualization, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Metadata, Network Security, Other Programming Languages, Plot (Graphics), Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software, Software Engineering, Software Security, Spreadsheet Software, Statistical Analysis, Statistical Programming, Storytelling, Strategy and Operations, Tableau Software, Theoretical Computer Science, Visual Design, Web Development

      4.8

      (70.4k 條評論)

      Beginner · Professional Certificate · 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, Machine Learning, Machine Learning Algorithms, Natural Language Processing, Plot (Graphics), Probability & Statistics, Probability Distribution, R Programming, Regression, Regression Analysis, Statistical Analysis, Statistical Programming, Statistical Tests, Theoretical Computer Science

      4.4

      (7k 條評論)

      Intermediate · Specialization · 3-6 Months

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      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      您將獲得的技能: Analysis, Business Analysis, Communication, Data Analysis, Econometrics, General Statistics, Machine Learning, Machine Learning Algorithms, Marketing, Modeling, Probability & Statistics, Regression, Statistical Analysis

      4.0

      (19 條評論)

      Intermediate · Specialization · 3-6 Months

    與 statistics for data science 相關的搜索

    statistics for data science with python
    advanced statistics for data science
    statistics for genomic data science
    statistical modeling for data science applications
    statistical inference for estimation in data science
    advanced linear models for data science 2: statistical linear models
    1234…84

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

    • Introduction to Statistics: Stanford University
    • Statistics with Python: University of Michigan
    • Statistics for Data Science with Python: IBM Skills Network
    • Data Science Math Skills: Duke University
    • Advanced Statistics for Data Science: Johns Hopkins University
    • Improving your statistical inferences: Eindhoven University of Technology
    • Mathematics for Machine Learning: Imperial College London
    • Tools for Data Science: IBM Skills Network
    • Data Analysis with R: Duke University
    • Google Data Analytics: Google

    關於 數據科學所需的統計學 的常見問題

    • Statistics for data science refers to the mathematical analysis used to sort, analyze, interpret, and present data. It includes concepts like probability distribution, regression, and over or under-sampling. Descriptive statistics organizes data based on characteristics of the data set, such as normal distribution, central tendency, variability, and standard deviation. Inferential statistics incorporates the use of probability theory to infer characteristics of the data set.‎

    • Learning statistics for data science can lead to career opportunities in data science and related fields. As organizations increasingly rely on data to make decisions, they tend to seek out analysts who understand how to work with data and present it to stakeholders. Learning statistics for data science can also provide a good salary. As of 2020, the median pay for computer and information research scientists in the US is $122,840 and the job market remains positive, according to the Bureau of Labor Statistics. Mathematicians and statisticians have a similar job outlook and a median salary of $92,030 per year.‎

    • Data analysis, data architects, data scientists, and information officers typically use statistics for data science in their regular work. Data science is a broad field, and statistics can be useful in other roles that require analyzing and presenting data. This includes data warehouse analysts, data visualization developers, database managers, and machine learning engineers. Additional related fields include financial analysts, teachers, and researchers working for universities and corporate settings.‎

    • Through online courses, you can learn the fundamentals of statistics for data science, including the theories and techniques statisticians use in their work. Some courses explore fundamental concepts like Bayes’ Theorem and probability theory. Others present methods for calculating and evaluating data sets. You can brush up on your knowledge of programs statisticians use, like Excel and Python, or examine the application of statistics specific fields.‎

    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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