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    Results for "advanced statistics"

    • Status: Free Trial
      Free Trial
      M

      MathWorks

      Practical Data Science with MATLAB

      Skills you'll gain: Data Storytelling, Feature Engineering, Data Visualization, Supervised Learning, Dimensionality Reduction, Data Integration, Interactive Data Visualization, Exploratory Data Analysis, Data Import/Export, Technical Communication, Data Analysis, Applied Machine Learning, Data Visualization Software, Matlab, Regression Analysis, Data Processing, Descriptive Statistics, Data Cleansing, Predictive Modeling, Data Science

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Bayesian Statistics: Time Series Analysis

      Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Bayesian Statistics, Statistical Modeling, Statistical Analysis, Statistical Inference, Regression Analysis, Data Analysis, Mathematical Modeling, Probability Distribution

      4.4
      Rating, 4.4 out of 5 stars
      ·
      16 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Advanced Computer Vision with TensorFlow

      Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Applied Machine Learning, Deep Learning, Feature Engineering, Artificial Neural Networks, Visualization (Computer Graphics), Data Processing, Network Architecture

      4.7
      Rating, 4.7 out of 5 stars
      ·
      522 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Excel/VBA for Creative Problem Solving, Part 2

      Skills you'll gain: Excel Macros, Visual Basic (Programming Language), Data Import/Export, Programming Principles, Spreadsheet Software, UI Components, Automation, Data Structures, Debugging, Data Validation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • T

      Tecnológico de Monterrey

      Cálculo Diferencial e Integral unidos por el Teorema Fundamental del Cálculo

      Skills you'll gain: Calculus, Integral Calculus, Advanced Mathematics, Graphing, Numerical Analysis, Mathematics Education, Trigonometry, Mathematical Modeling, Mathematical Theory & Analysis, Algebra, Computational Thinking, Applied Mathematics, Derivatives

      4.6
      Rating, 4.6 out of 5 stars
      ·
      718 reviews

      Mixed · Course · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Principles of fMRI 1

      Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Data Analysis, Research Design, Image Analysis, Neurology, Science and Research, Statistical Analysis, Statistical Modeling, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      838 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Mathematical Biostatistics Boot Camp 1

      Skills you'll gain: Sampling (Statistics), Bayesian Statistics, Probability & Statistics, Statistical Inference, Statistical Methods, Probability, Probability Distribution, Statistical Analysis, Biostatistics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      515 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Converter Circuits

      Skills you'll gain: Power Electronics, Semiconductors, Electronic Components, Electrical Power, Electrical Engineering, Electronics, Simulation and Simulation Software, Schematic Diagrams

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

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Use Canva to Design Digital Course Collateral

      Skills you'll gain: Canva (Software), Color Theory, Developing Training Materials, Digital Design, Design Elements And Principles, Graphic Design, Creative Design

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.5K reviews

      Advanced · Guided Project · Less Than 2 Hours

    • D

      Duke University

      The Brain and Space

      Skills you'll gain: Spatial Analysis, Neurology, Human Learning, Experimentation, Laboratory Research, Physics, Biology, General Science and Research, Magnetic Resonance Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      652 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Advanced Embedded Linux Development

      Skills you'll gain: Agile Methodology, Scrum (Software Development), Embedded Systems, System Programming, Software Testing, Linux, Software Development Methodologies, Docker (Software), Git (Version Control System), Containerization, Operating Systems, File Systems, C++ (Programming Language), Shell Script, Debugging, OS Process Management, Internet Of Things, IBM WebSphere MQ, Peripheral Devices, Build Tools

      4.3
      Rating, 4.3 out of 5 stars
      ·
      143 reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Probability Theory: Foundation for Data Science

      Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Statistics, Bayesian Statistics, Data Science, Statistical Analysis, Statistical Inference

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      253 reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…353637…269

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

    • Practical Data Science with MATLAB: MathWorks
    • Bayesian Statistics: Time Series Analysis: University of California, Santa Cruz
    • Advanced Computer Vision with TensorFlow: DeepLearning.AI
    • Excel/VBA for Creative Problem Solving, Part 2: University of Colorado Boulder
    • Cálculo Diferencial e Integral unidos por el Teorema Fundamental del Cálculo: Tecnológico de Monterrey
    • Principles of fMRI 1: Johns Hopkins University
    • Mathematical Biostatistics Boot Camp 1: Johns Hopkins University
    • Converter Circuits: University of Colorado Boulder
    • Use Canva to Design Digital Course Collateral: Coursera Project Network
    • The Brain and Space: Duke University

    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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