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    267 Ergebnisse für „advanced statistics“

    • Johns Hopkins University

      Johns Hopkins University

      Advanced Statistics for Data Science

      Kompetenzen, die Sie erwerben: Algebra, Artificial Neural Networks, Bayesian Statistics, Biostatistics, Business Analysis, Calculus, Communication, Data Analysis, Dimensionality Reduction, Econometrics, Experiment, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Marketing, Mathematics, Probability & Statistics, Probability Distribution, Python Programming, Regression, Statistical Machine Learning, Statistical Programming, Statistical Tests

      4.4

      (655 Bewertungen)

      Advanced · Specialization · 3+ Months

    • Kostenlos

      Georgia Institute of Technology

      Georgia Institute of Technology

      Materials Data Sciences and Informatics

      Kompetenzen, die Sie erwerben: User Experience, Probability & Statistics, Dimensionality Reduction, Experiment, General Statistics, Machine Learning, Human Computer Interaction, Materials

      4.5

      (290 Bewertungen)

      Intermediate · Course · 1-3 Months

    • Kostenlos

      Nanjing University

      Nanjing University

      Data Processing Using Python

      Kompetenzen, die Sie erwerben: Computer Programming, Python Programming, Statistical Programming

      4.2

      (260 Bewertungen)

      Beginner · Course · 1-3 Months

    • University of Colorado Boulder

      University of Colorado Boulder

      Business Analytics for Decision Making

      Kompetenzen, die Sie erwerben: Big Data, Business Analysis, Data Analysis, Analytics, Data Management, Probability & Statistics, Business Analytics, Finance, Algorithms, Risk Management, Machine Learning Algorithms, Theoretical Computer Science, Mathematics, Analysis, Machine Learning, Mathematical Theory & Analysis, Markov Model

      4.6

      (1.7k Bewertungen)

      Mixed · Course · 1-4 Weeks

    • Kostenlos

      Stanford University

      Stanford University

      Introduction to Statistics

      Kompetenzen, die Sie erwerben: Data Analysis, Experiment, Probability & Statistics, General Statistics, Econometrics, Statistical Tests, Analysis, Bayesian Statistics, Probability Distribution, Basic Descriptive Statistics, Probability, Statistical Analysis, Markov Model, Machine Learning, Regression

      4.5

      (987 Bewertungen)

      Beginner · Course · 1-3 Months

    • Coursera Project Network

      Coursera Project Network

      Create a Custom Marketing Analytics Dashboard in Data Studio

      Kompetenzen, die Sie erwerben: Data Visualization, Market (Economics), Market Analysis, Analysis, Marketing

      4.4

      (52 Bewertungen)

      Intermediate · Rhyme Project · Less Than 2 Hours

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      Johns Hopkins University

      Johns Hopkins University

      Data Science: Foundations using R

      Kompetenzen, die Sie erwerben: Analysis, Application Development, Business Analysis, Computer Programming, Data Analysis, Data Management, Data Visualization, Exploratory Data Analysis, Extract, Transform, Load, Github, Knitr, Probability & Statistics, R Programming, Rstudio, Software Engineering Tools, Statistical Programming

      4.6

      (46.4k Bewertungen)

      Beginner · Specialization · 3+ Months

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      University of Michigan

      University of Michigan

      Statistics with Python

      Kompetenzen, die Sie erwerben: Bayesian Statistics, Business Analysis, Communication, Computer Programming, Confidence, Data Analysis, Data Visualization, Econometrics, Experiment, General Statistics, Hypothesis, Inference, Machine Learning, Machine Learning Algorithms, Marketing, Modeling, Probability & Statistics, Programming Principles, Python Programming, Regression, Statistical Analysis, Statistical Hypothesis Testing, Statistical Inference, Statistical Programming, Statistical Tests, Statistical Visualization

      4.6

      (2.7k Bewertungen)

      Beginner · Specialization · 1-3 Months

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      IBM

      IBM

      Advanced Data Science with IBM

      Kompetenzen, die Sie erwerben: Algorithms, Apache, Apache Spark, 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, Deep Learning, Dimensionality Reduction, Distributed Computing Architecture, Econometrics, Estimation, Experiment, General Statistics, IBM Cloud, Leadership and Management, Machine Learning, Machine Learning Algorithms, Mathematics, Natural Language Processing, Probability & Statistics, Probability Distribution, Programming Principles, Python Programming, Regression, Signal Processing, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Strategy and Operations, Theoretical Computer Science

      4.3

      (2.9k Bewertungen)

      Advanced · Specialization · 3+ Months

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      Johns Hopkins University

      Johns Hopkins University

      Data Science: Statistics and Machine Learning

      Kompetenzen, die Sie erwerben: Analysis, Business Analysis, Data Analysis, Data Visualization, Econometrics, Experiment, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, Natural Language Processing, Plot (Graphics), Probability & Statistics, R Programming, Regression, Regression Analysis, Statistical Analysis, Statistical Programming, Theoretical Computer Science

      4.4

      (7k Bewertungen)

      Intermediate · Specialization · 3+ Months

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      Google Cloud

      Google Cloud

      Advanced Machine Learning on Google Cloud

      Kompetenzen, die Sie erwerben: Apache, Applied Machine Learning, Artificial Neural Networks, Business Psychology, Cloud Computing, Computational Thinking, Computer Architecture, Computer Programming, Computer Vision, Data Analysis, Data Management, Deep Learning, Distributed Computing Architecture, Entrepreneurship, General Statistics, Google Cloud Platform, Hardware Design, Linear Algebra, Machine Learning, Mathematics, Natural Language Processing, Performance Management, Probability & Statistics, Python Programming, Recommender Systems, Software Architecture, Software Engineering, Statistical Programming, Strategy and Operations, Theoretical Computer Science

      4.4

      (2.2k Bewertungen)

      Advanced · Specialization · 3+ Months

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      University of Colorado Boulder

      University of Colorado Boulder

      Advanced Business Analytics

      Kompetenzen, die Sie erwerben: Algorithms, Analysis, Applied Machine Learning, Artificial Neural Networks, Big Data, Business Analysis, Business Communication, Cloud Computing, Communication, Computer Vision, Data Analysis, Data Analysis Software, Data Management, Data Visualization, Databases, Finance, General Statistics, Machine Learning, Machine Learning Algorithms, Markov Model, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Regression, Risk Management, SQL, Spreadsheet Software, Statistical Analysis, Statistical Programming, Theoretical Computer Science

      4.6

      (4.7k Bewertungen)

      Intermediate · Specialization · 3+ Months

    Suchanfragen mit Bezug zu advanced statistics

    advanced statistics for data science
    advanced linear models for data science 2: statistical linear models
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    Zusammenfassend sind hier 10 unserer beliebtesten advanced statistics Kurse

    • 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
    • Introduction to Statistics: Stanford University
    • Create a Custom Marketing Analytics Dashboard in Data Studio: Coursera Project Network
    • Data Science: Foundations using R: Johns Hopkins University
    • Statistics with Python: University of Michigan
    • Advanced Data Science with IBM: IBM
    • Data Science: Statistics and Machine Learning: Johns Hopkins University

    Häufig gestellte Fragen zum Thema Statistik für Fortgeschrittene

    • 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.‎

    Diese häufig gestellten Fragen dienen nur zu Informationszwecken. Den Lernenden wird empfohlen, eingehender zu recherchieren, ob Kurse und andere angestrebte Qualifikationen wirklich ihren persönlichen, beruflichen und finanziellen Vorstellungen entsprechen.
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