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    Results for "advanced statistics"

    • S

      Stanford University

      Probabilistic Graphical Models 3: Learning

      Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Markov Model, Machine Learning, Statistical Modeling, Network Analysis, Probability Distribution, Statistical Methods, Probability & Statistics, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      303 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Text Retrieval and Search Engines

      Skills you'll gain: Text Mining, Natural Language Processing, Data Mining, Unstructured Data, Big Data, Web Analytics and SEO, Machine Learning, Information Architecture, Statistical Methods, Algorithms, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      959 reviews

      Mixed · Course · 1 - 3 Months

    • I

      Imperial College London

      Logistic Regression in R for Public Health

      Skills you'll gain: Descriptive Statistics, Exploratory Data Analysis, Regression Analysis, R Programming, Statistical Modeling, Predictive Modeling, Statistical Analysis, Biostatistics, Feature Engineering, Statistical Inference, Data Analysis Software, Public Health

      4.8
      Rating, 4.8 out of 5 stars
      ·
      363 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Everyday Excel, Part 2

      Skills you'll gain: Regression Analysis, Depreciation, Microsoft Excel, Statistical Modeling, Excel Formulas, Financial Analysis, Cash Flows, Predictive Modeling, Data Management, Financial Modeling, Business Mathematics, Financial Forecasting, Process Optimization, Data Analysis, Complex Problem Solving

      4.7
      Rating, 4.7 out of 5 stars
      ·
      560 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      D

      Duke University

      Programming for Python Data Science: Principles to Practice

      Skills you'll gain: Matplotlib, Pandas (Python Package), NumPy, Computational Thinking, Predictive Modeling, Data Cleansing, Data Structures, Data Visualization Software, Visualization (Computer Graphics), Debugging, Data Analysis, Object Oriented Programming (OOP), Data Manipulation, Regression Analysis, Python Programming, Data Science, Algorithms, Simulations, Statistical Methods, Program Development

      3.9
      Rating, 3.9 out of 5 stars
      ·
      66 reviews

      Beginner · Specialization · 3 - 6 Months

    • P

      Packt

      Advanced Data Analysis and Visualization with Pandas

      Skills you'll gain: Matplotlib, Pandas (Python Package), Data Import/Export, Data Visualization Software, Microsoft Excel, NumPy, Time Series Analysis and Forecasting, Data Analysis, Data Manipulation, Python Programming

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Pattern Discovery in Data Mining

      Skills you'll gain: Data Mining, Big Data, Anomaly Detection, Text Mining, Unstructured Data, Spatial Analysis, Advanced Analytics, Image Analysis, Algorithms, Information Privacy

      4.3
      Rating, 4.3 out of 5 stars
      ·
      325 reviews

      Mixed · Course · 1 - 3 Months

    • K

      King Abdullah University of Science and Technology

      Fundamental Skills in Bioinformatics

      Skills you'll gain: Statistical Analysis, Bioinformatics, Unix, Scientific Visualization, Statistical Methods, R Programming, Rmarkdown, Unix Commands, Data Analysis, Data Quality, Statistical Hypothesis Testing, Exploratory Data Analysis, Data Visualization, Programming Principles, Pandas (Python Package), Python Programming, NumPy, Data Manipulation, Data Structures

      4.4
      Rating, 4.4 out of 5 stars
      ·
      59 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Machine Learning With Big Data

      Skills you'll gain: Exploratory Data Analysis, Apache Spark, Big Data, Regression Analysis, Data Mining, Applied Machine Learning, Statistical Analysis, Machine Learning, Data Analysis, Unsupervised Learning, Data Transformation, Predictive Modeling, Data Cleansing, Supervised Learning, Decision Tree Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.5K reviews

      Mixed · Course · 1 - 3 Months

    • I

      IE Business School

      Globalización, Crecimiento Económico y Estabilidad

      Skills you'll gain: Financial Policy, Economics, Policy, and Social Studies, Economics, Public Policies, International Finance, Policy Analysis, International Relations, Economic Development, Tax, Socioeconomics, Trend Analysis, Global Marketing, Business Economics, Political Sciences, Analysis, Fiscal Management, Supply And Demand, Business Risk Management, World History, Policty Analysis, Research, and Development

      4.8
      Rating, 4.8 out of 5 stars
      ·
      693 reviews

      Beginner · Specialization · 3 - 6 Months

    • S

      SAS

      Doing More with SAS Programming

      Skills you'll gain: SAS (Software), Data Manipulation, Consolidation, Data Transformation, Data Processing, Data Analysis, Data Presentation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      939 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      V

      Vanderbilt University

      Case Studies in Personalized Medicine

      Skills you'll gain: Precision Medicine, Medical Science and Research, Health Informatics, Biostatistics, Electronic Medical Record, Healthcare Ethics, General Medicine, Clinical Research, Probability & Statistics, Statistical Analysis, Molecular Biology, Pharmacology

      4.8
      Rating, 4.8 out of 5 stars
      ·
      496 reviews

      Mixed · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
    statistical analysis and advanced techniques
    advanced linear models for data science 2: statistical linear models
    1…484950…263

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

    • Probabilistic Graphical Models 3: Learning: Stanford University
    • Text Retrieval and Search Engines: University of Illinois Urbana-Champaign
    • Logistic Regression in R for Public Health: Imperial College London
    • Everyday Excel, Part 2: University of Colorado Boulder
    • Programming for Python Data Science: Principles to Practice: Duke University
    • Advanced Data Analysis and Visualization with Pandas: Packt
    • Pattern Discovery in Data Mining: University of Illinois Urbana-Champaign
    • Fundamental Skills in Bioinformatics: King Abdullah University of Science and Technology
    • Machine Learning With Big Data: University of California San Diego
    • Globalización, Crecimiento Económico y Estabilidad: IE Business School

    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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