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    Results for "advanced statistics"

    • I

      IBM

      Applied Data Science with R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Shiny (R Package), Data Wrangling, Dashboard, Exploratory Data Analysis, Relational Databases, Data Analysis, Ggplot2, Database Design, Data Presentation, SQL, Plot (Graphics), Leaflet (Software), Data Transformation, Database Management, Data Manipulation, Web Scraping, R Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Build Basic Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Data Ethics, Computer Vision, Artificial Intelligence, Unsupervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • K

      Korea Advanced Institute of Science and Technology(KAIST)

      Electrodynamics

      Skills you'll gain: Electrical Engineering, Basic Electrical Systems, Electronic Components, Electrical Systems, Differential Equations, Physics, Engineering Analysis, Integral Calculus, Applied Mathematics, Advanced Mathematics, Scientific Visualization, Engineering Calculations, Calculus, Electronic Systems, Mechanics, Electronics, Energy and Utilities, Mathematical Modeling, Linear Algebra

      4.7
      Rating, 4.7 out of 5 stars
      ·
      948 reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      Linear Regression and Modeling

      Skills you'll gain: Regression Analysis, Data Analysis Software, Statistical Analysis, R Programming, Statistical Modeling, Statistical Inference, Correlation Analysis, Statistical Methods, Mathematical Modeling, Exploratory Data Analysis, Predictive Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Advanced Machine Learning on Google Cloud

      Skills you'll gain: Natural Language Processing, MLOps (Machine Learning Operations), Tensorflow, Large Language Modeling, Reinforcement Learning, Computer Vision, Google Cloud Platform, Keras (Neural Network Library), Systems Design, Image Analysis, Hybrid Cloud Computing, Applied Machine Learning, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms, Distributed Computing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Business Analytics

      Skills you'll gain: Data Storytelling, Extract, Transform, Load, Marketing Analytics, Data Presentation, Data Visualization, Regression Analysis, Alteryx, Data Collection, Interactive Data Visualization, Data Quality, Statistical Visualization, Tidyverse (R Package), R Programming, Data Visualization Software, Data Processing, Network Analysis, Business Analytics, Internal Controls, Exploratory Data Analysis, Robotic Process Automation

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      A Crash Course in Data Science

      Skills you'll gain: Data Science, Data Management, Data-Driven Decision-Making, Project Design, Performance Metric, Software Engineering, Machine Learning, Predictive Modeling, Statistical Inference

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      Duke University

      Business Metrics for Data-Driven Companies

      Skills you'll gain: Business Analytics, Business Metrics, Analytics, Business Process Improvement, Business Intelligence, Tableau Software, Data Analysis, Big Data, Key Performance Indicators (KPIs), Spreadsheet Software, Web Analytics, Data-Driven Decision-Making, Business Strategy, Digital Transformation, E-Commerce, Financial Services, SQL

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.4K reviews

      Mixed · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Basic Statistics in Python (Correlations and T-tests)

      Skills you'll gain: Exploratory Data Analysis, Box Plots, Correlation Analysis, Data Visualization, Scatter Plots, Data Cleansing, Data Manipulation, Pandas (Python Package), Statistical Hypothesis Testing, Descriptive Statistics, Statistical Analysis, Data Analysis, Probability & Statistics, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      34 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • G

      Georgia Institute of Technology

      Fundamentals of Engineering Exam Review

      Skills you'll gain: Structural Analysis, Probability & Statistics, Structural Engineering, Hydraulics, Statistical Methods, Statistics, Engineering Analysis, Mechanical Engineering, Probability, Engineering, Probability Distribution, Mechanics, Engineering Calculations, Civil Engineering, Applied Mathematics, Algebra, Advanced Mathematics, Calculus, Differential Equations, Geometry

      4.6
      Rating, 4.6 out of 5 stars
      ·
      611 reviews

      Mixed · Course · 1 - 3 Months

    • K

      Kennesaw State University

      Six Sigma Tools for Define and Measure

      Skills you'll gain: Data Collection, Lean Six Sigma, Six Sigma Methodology, Quality Improvement, Process Improvement, Business Process, Project Management, Project Planning, Customer experience improvement, Data Validation, Process Mapping, Statistics, Stakeholder Management, Statistical Analysis

      Build toward a degree

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

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Survey Data Collection and Analytics

      Skills you'll gain: Sampling (Statistics), Sample Size Determination, Surveys, Survey Creation, Research Methodologies, Data Collection, Statistical Analysis, Statistical Software, Interviewing Skills, Data Integration, Data Ethics, Research Design, Stata, R Programming, Data Quality, Statistical Modeling, Qualitative Research, Descriptive Statistics, Statistical Programming, Data Cleansing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.4K reviews

      Beginner · Specialization · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…222324…262

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

    • Applied Data Science with R: IBM
    • Build Basic Generative Adversarial Networks (GANs): DeepLearning.AI
    • Electrodynamics: Korea Advanced Institute of Science and Technology(KAIST)
    • Linear Regression and Modeling : Duke University
    • Advanced Machine Learning on Google Cloud: Google Cloud
    • Business Analytics: University of Illinois Urbana-Champaign
    • A Crash Course in Data Science: Johns Hopkins University
    • Business Metrics for Data-Driven Companies: Duke University
    • Basic Statistics in Python (Correlations and T-tests): Coursera Project Network
    • Fundamentals of Engineering Exam Review: Georgia Institute of Technology

    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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