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    Results for "advanced statistics"

    • M

      Michigan State University

      Photography Techniques: Light, Content, and Sharing

      Skills you'll gain: Photography, Photo Editing, Peer Review, Color Theory, Storytelling, Creativity, Information Privacy, Web Design and Development

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      IBM

      Introduction to R Programming for Data Science

      Skills you'll gain: Data Manipulation, Web Scraping, R Programming, Data Analysis, Data Science, Data Structures, Data Import/Export, Exploratory Data Analysis, Programming Principles, Jupyter, Integrated Development Environments

      4.5
      Rating, 4.5 out of 5 stars
      ·
      562 reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Advanced Relational Database and SQL

      Skills you'll gain: Stored Procedure, SQL, Data Presentation, Query Languages, Relational Databases, Database Development

      4.5
      Rating, 4.5 out of 5 stars
      ·
      372 reviews

      Advanced · Guided Project · Less Than 2 Hours

    • I

      IBM

      IBM AI Enterprise Workflow

      Skills you'll gain: Feature Engineering, Data Visualization, Data Ethics, Exploratory Data Analysis, Unsupervised Learning, Data Presentation, Tensorflow, Application Deployment, Dimensionality Reduction, MLOps (Machine Learning Operations), Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Dashboard, Unit Testing, Artificial Neural Networks, Data Science, Artificial Intelligence

      4.3
      Rating, 4.3 out of 5 stars
      ·
      319 reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: Free
      Free
      Y

      Yonsei University

      Deep Learning for Business

      Skills you'll gain: Deep Learning, Tensorflow, Artificial Neural Networks, Business Strategy, Image Analysis, Natural Language Processing, Artificial Intelligence, Machine Learning, Reinforcement Learning, Unsupervised Learning, Supervised Learning

      4.4
      Rating, 4.4 out of 5 stars
      ·
      680 reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      AI-Powered Software and System Design

      Skills you'll gain: Database Design, Software Design Patterns, Database Systems, Software Architecture, API Design, System Design and Implementation, Large Language Modeling, Software Development, Artificial Intelligence, Generative AI, Secure Coding, Application Programming Interface (API), Performance Tuning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      125 reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Understanding Prostate Cancer

      Skills you'll gain: Patient Education And Counseling, Oncology, Preventative Care, Patient Evaluation, Primary Care, Pathology, Urology, Patient Treatment, Health Care, Internal Medicine, General Medical Tests and Procedures, Treatment Planning, Laboratory Testing, Biology, Precision Medicine, Surgery, Care Management, Clinical Trials, Anatomy, Risk Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      705 reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google

      Google Data Analytics

      Skills you'll gain: Data Presentation, Data Storytelling, Presentations, Data Cleansing, Data Visualization, Rmarkdown, Data-Driven Decision-Making, Data Validation, Data Ethics, Analytical Skills, Dashboard, Spreadsheet Software, Ggplot2, SQL, Data Visualization Software, Data Literacy, Data Collection, Sampling (Statistics), Data Analysis, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      312 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free
      Free
      U

      University of Pennsylvania

      Single Variable Calculus

      Skills you'll gain: Calculus, Numerical Analysis, Applied Mathematics, Engineering Calculations, Integral Calculus, Engineering Analysis, Differential Equations, Mathematical Theory & Analysis, Advanced Mathematics, Estimation, Derivatives

      4.6
      Rating, 4.6 out of 5 stars
      ·
      416 reviews

      Mixed · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Data – What It Is, What We Can Do With It

      Skills you'll gain: Data Literacy, Data Analysis, Research Design, Descriptive Statistics, Analytics, Analysis, Statistics, Quantitative Research, Statistical Methods, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      172 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      Universidade Estadual de Campinas

      Pensamento Crítico, Lógica e Argumentação

      Skills you'll gain: Logical Reasoning, Deductive Reasoning, Liberal Arts, Persuasive Communication, Research, Statistics, Media and Communications, Appeals, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      126 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      T

      The University of Edinburgh

      Data Science in Stratified Healthcare and Precision Medicine

      Skills you'll gain: Precision Medicine, Bioinformatics, Image Analysis, Medical Imaging, Big Data, Health Informatics, Statistical Methods, Data Science, Machine Learning, Natural Language Processing, Probability & Statistics, Data Analysis, Molecular Biology, Network Analysis, Graph Theory, Healthcare Ethics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      334 reviews

      Intermediate · 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…454647…263

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

    • Photography Techniques: Light, Content, and Sharing: Michigan State University
    • Introduction to R Programming for Data Science: IBM
    • Advanced Relational Database and SQL: Coursera Project Network
    • IBM AI Enterprise Workflow: IBM
    • Deep Learning for Business: Yonsei University
    • AI-Powered Software and System Design: DeepLearning.AI
    • Understanding Prostate Cancer: Johns Hopkins University
    • Google Data Analytics: Google
    • Single Variable Calculus: University of Pennsylvania
    • Data – What It Is, What We Can Do With It: Johns Hopkins 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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