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    Results for "advanced statistics"

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      Coursera Project Network

      أساسيات تحليل البيانات باستخدام جداول بيانات جوجل

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      4.6
      Rating, 4.6 out of 5 stars
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      153 reviews

      Beginner · Guided Project · Less Than 2 Hours

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      Microsoft

      AI and Machine Learning Algorithms and Techniques

      Skills you'll gain: Unsupervised Learning, Generative AI, Large Language Modeling, Supervised Learning, Deep Learning, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Statistical Machine Learning, Predictive Modeling, Machine Learning Algorithms, Artificial Neural Networks, Feature Engineering, Decision Tree Learning, Business Logic, Dimensionality Reduction, Data Modeling, Performance Metric

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      Intermediate · Course · 1 - 3 Months

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      Coursera Instructor Network

      Advanced Data Analysis and Collaboration in Qlik Sense

      Skills you'll gain: Data Storytelling, Data Visualization Software, Dashboard, Data Analysis, Advanced Analytics, Interactive Data Visualization, Data Visualization, Analytics, Data Manipulation, Collaborative Software, Data Presentation, Data Sharing

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      Advanced · Course · 1 - 4 Weeks

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      École normale supérieure

      Statistical Mechanics: Algorithms and Computations

      Skills you'll gain: Sampling (Statistics), Physics, Simulations, Statistical Programming, Computational Logic, Numerical Analysis, Markov Model, Mechanics, Quantitative Research, Algorithms, Programming Principles, Applied Mathematics, Linear Algebra, Integral Calculus

      4.8
      Rating, 4.8 out of 5 stars
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      264 reviews

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      University of California, Irvine

      Advanced Instructional Strategies in the Virtual Classroom

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      575 reviews

      Mixed · Course · 1 - 3 Months

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      Yonsei University

      Smart Device & Mobile Emerging Technologies

      Skills you'll gain: Wireless Networks, Telecommunications, Mobile Development, Apple iOS, Display Devices, Business Planning, iOS Development, Product Planning, Android (Operating System), Company, Product, and Service Knowledge, Business Strategy, Network Analysis, Emerging Technologies, Operating Systems, Knowledge of Apple Hardware, System Software, Digital Communications, General Networking, Peripheral Devices, Market Trend

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      Beginner · Course · 1 - 3 Months

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      University of Colorado Boulder

      Kinetics: Studying Spacecraft Motion

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      4.8
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      132 reviews

      Advanced · Course · 1 - 4 Weeks

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      University of Colorado Boulder

      The Data Driven Manager

      Skills you'll gain: Sampling (Statistics), Engineering Management, Data-Driven Decision-Making, Data Literacy, Probability Distribution, Descriptive Statistics, Statistical Hypothesis Testing, Estimation, Data Analysis, Sample Size Determination, Correlation Analysis, Data Visualization, Statistical Software, Statistical Methods, Statistical Analysis, Leadership and Management, Technical Management, Statistical Visualization, Statistics, Leadership

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      37 reviews

      Beginner · Specialization · 3 - 6 Months

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      University of California, Santa Cruz

      Bayesian Statistics: Mixture Models

      Skills you'll gain: R Programming, Statistical Modeling, Bayesian Statistics, Statistical Machine Learning, Markov Model, Mathematical Modeling, Statistical Methods, Probability & Statistics, Unsupervised Learning, Machine Learning Algorithms

      4.5
      Rating, 4.5 out of 5 stars
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      61 reviews

      Intermediate · Course · 1 - 3 Months

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      University of Pennsylvania

      Calculus: Single Variable Part 4 - Applications

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      4.9
      Rating, 4.9 out of 5 stars
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      274 reviews

      Mixed · Course · 1 - 3 Months

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      University of California, Davis

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      4.6
      Rating, 4.6 out of 5 stars
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      73 reviews

      Intermediate · Course · 1 - 4 Weeks

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      Macquarie University

      Business intelligence and data analytics: Generate insights

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      4.6
      Rating, 4.6 out of 5 stars
      ·
      450 reviews

      Mixed · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…102103104…269

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

    • أساسيات تحليل البيانات باستخدام جداول بيانات جوجل : Coursera Project Network
    • AI and Machine Learning Algorithms and Techniques: Microsoft
    • Advanced Data Analysis and Collaboration in Qlik Sense : Coursera Instructor Network
    • Statistical Mechanics: Algorithms and Computations: École normale supérieure
    • Advanced Instructional Strategies in the Virtual Classroom: University of California, Irvine
    • Smart Device & Mobile Emerging Technologies: Yonsei University
    • Kinetics: Studying Spacecraft Motion: University of Colorado Boulder
    • The Data Driven Manager: University of Colorado Boulder
    • Bayesian Statistics: Mixture Models: University of California, Santa Cruz
    • Calculus: Single Variable Part 4 - Applications: University of Pennsylvania

    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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