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    Results for "advanced statistics"

    • Status: Free Trial
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      I

      IBM

      Applied Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Visualization, Predictive Modeling, Interactive Data Visualization, Exploratory Data Analysis, Data Wrangling, Data Analysis, Jupyter, Matplotlib, Pandas (Python Package), Seaborn, Data Presentation, Data Import/Export, Web Scraping, Automation, Data Science, Data-Driven Decision-Making, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      DeepLearning.AI TensorFlow Developer

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Keras (Neural Network Library), Natural Language Processing, Time Series Analysis and Forecasting, Deep Learning, Artificial Neural Networks, Generative AI, Applied Machine Learning, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Text Mining, Forecasting, Data Processing, Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      25K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Google Sheets - Advanced Topics

      Skills you'll gain: Google Sheets, Excel Formulas, Spreadsheet Software, Google Workspace, Data Validation, Data Visualization, Productivity Software, Data Analysis Software, Data Integration, Data Import/Export, Automation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      348 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      Generative AI Automation

      Skills you'll gain: Prompt Engineering, ChatGPT, Ideation, Verification And Validation, Data Validation, Data Presentation, Productivity, Generative AI, Document Management, Data Synthesis, Image Analysis, Data Capture, Artificial Intelligence, OpenAI, Large Language Modeling, Data Analysis, Organizational Skills, Risk Management Framework, Computer Vision, Microsoft Excel

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis and Visualization Foundations

      Skills you'll gain: Data Storytelling, Big Data, Data Visualization Software, Data Analysis, Dashboard, IBM Cognos Analytics, Statistical Analysis, Data Mining, Apache Hadoop, Tree Maps, Excel Formulas, Data Wrangling, Apache Hive, Data Collection, Data Mart, Microsoft Excel, Data Warehousing, Data Quality, Data Cleansing, Data Import/Export

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      27K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Science Fundamentals with Python and SQL

      Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Statistical Hypothesis Testing, Databases, Stored Procedure, Web Scraping, Relational Databases, Automation, Data Science, GitHub, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      71K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      Generative AI Leadership & Strategy

      Skills you'll gain: Prompt Engineering, ChatGPT, Ideation, Verification And Validation, Data Validation, Succession Planning, Productivity, Business Writing, Generative AI, Leadership, Meeting Facilitation, Organizational Leadership, Artificial Intelligence, Large Language Modeling, Business Leadership, Proposal Writing, Communication, Risk Management Framework, Creative Thinking, Human Resource Strategy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.5K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to Data Science

      Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Peer Review, Data Modeling, Databases, Stored Procedure, Relational Databases, Database Design, Query Languages, Data Science, Database Management, Big Data, Data Cleansing, Data Visualization Software, GitHub, Business Analysis, Cloud Computing, Data Analysis

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      99K reviews

      Beginner · Specialization · 3 - 6 Months

    • T

      The University of Sydney

      Introduction to Advanced Calculus

      Skills you'll gain: Advanced Mathematics, Integral Calculus, Calculus, Mathematical Theory & Analysis, Differential Equations, Applied Mathematics, Engineering Calculations, Mathematical Modeling, Linear Algebra, Physics, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California, Davis

      Learn SQL Basics for Data Science

      Skills you'll gain: Data Governance, Presentations, SQL, Apache Spark, Distributed Computing, Data Quality, Descriptive Statistics, Data Lakes, A/B Testing, Data Storytelling, Data Analysis, Peer Review, Exploratory Data Analysis, Data Pipelines, Databricks, JSON, Statistical Analysis, Database Design, Query Languages, Complex Problem Solving

      4.6
      Rating, 4.6 out of 5 stars
      ·
      17K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Statistics and Data Analysis with Excel, Part 1

      Skills you'll gain: Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Probability, Box Plots, Histogram, Probability Distribution, Probability & Statistics, Scatter Plots, Statistics, Microsoft Excel, Excel Formulas, Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28 reviews

      Beginner · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
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    In summary, here are 10 of our most popular advanced statistics courses

    • Applied Data Science: IBM
    • Data Analysis with R: Duke University
    • DeepLearning.AI TensorFlow Developer: DeepLearning.AI
    • Google Sheets - Advanced Topics: Google Cloud
    • Generative AI Automation: Vanderbilt University
    • Data Analysis and Visualization Foundations: IBM
    • Data Science Fundamentals with Python and SQL: IBM
    • Generative AI Leadership & Strategy: Vanderbilt University
    • Introduction to Data Science: IBM
    • Introduction to Advanced Calculus: The University of Sydney

    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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