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    Results for "advanced statistics"

    • U

      University of Washington

      Machine Learning: Clustering & Retrieval

      Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Big Data, Statistical Inference, Text Mining, Statistical Modeling, Machine Learning Algorithms, Unstructured Data, Machine Learning, Sampling (Statistics), Scalability, Probability Distribution, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      N

      Nanjing University

      Data Processing Using Python

      Skills you'll gain: Data Processing, Data Mining, Data Structures, Data Presentation, Object Oriented Programming (OOP), Web Scraping, Data Analysis, Python Programming, Pandas (Python Package), NumPy, Data Visualization, Data Import/Export, Data Manipulation, Matplotlib, User Interface (UI) Design

      4.1
      Rating, 4.1 out of 5 stars
      ·
      371 reviews

      Beginner · Course · 1 - 3 Months

    • Q

      Queen Mary University of London

      Market Research

      Skills you'll gain: Qualitative Research, Proposal Development, Market Research, Research Reports, Data Collection, Research Design, Research Methodologies, Data Analysis, Statistical Hypothesis Testing, Survey Creation, Statistical Analysis, Surveys, Correlation Analysis, Quantitative Research, Research, Science and Research, Market Analysis, Focus Group, Regression Analysis, Content Performance Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      435 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Introduction to Time Value of Money (TVM)

      Skills you'll gain: Loans, Microsoft Excel, Finance, Capital Budgeting, Financial Analysis, Business Mathematics, General Finance, Cash Flows, Forecasting, Financial Planning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      934 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Minnesota

      Advanced Models for Decision Making

      Skills you'll gain: Operations Research, Supply Chain, Business Analytics, Mathematical Modeling, Manufacturing Operations, Workforce Planning, Microsoft Excel, Resource Allocation, Finance, Production Planning, Investment Management, Decision Making

      4.8
      Rating, 4.8 out of 5 stars
      ·
      52 reviews

      Beginner · Course · 1 - 4 Weeks

    • S

      SAP

      Understanding the Enterprise Systems Environment

      Skills you'll gain: Digital Transformation, Cloud Computing Architecture, Systems Design, Cloud Computing, SAP Applications, Cybersecurity, Software As A Service, Systems Analysis, Enterprise Architecture, Enterprise Resource Planning, Business Technologies, Data Modeling, Business Process Automation, Application Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      201 reviews

      Beginner · Course · 1 - 3 Months

    • S

      Starweaver

      Customer Relationship Management

      Skills you'll gain: Customer Relationship Management, Loyalty Programs, Customer experience strategy (CX), Customer Data Management, Customer Insights, Customer Engagement, Customer Service, Customer Retention, Customer experience improvement, Personalized Service, Marketing Strategies, Data-Driven Decision-Making, Technology Strategies, Business Technologies, Automation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      205 reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Microsoft

      Microsoft Front-End Developer

      Skills you'll gain: GitHub, C# (Programming Language), Secure Coding, HTML and CSS, User Interface and User Experience (UI/UX) Design, Figma (Design Software), Open Web Application Security Project (OWASP), Git (Version Control System), Object Oriented Programming (OOP), Web Development, Web Design, Debugging, Mockups, Web Content Accessibility Guidelines, Microsoft Copilot, Adobe XD, Authentications, Front-End Web Development, Programming Principles, UI Components

      4.3
      Rating, 4.3 out of 5 stars
      ·
      85 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Colorado System

      Fundamentals of Computer Network Security

      Skills you'll gain: Cryptography, Public Key Infrastructure, Cybersecurity, Application Security, Data Security, Firewall, Cyber Attacks, Data Encryption Standard, Penetration Testing, Network Security, Information Assurance, Encryption, Risk Management Framework, Advanced Encryption Standard (AES), Intrusion Detection and Prevention, Vulnerability Scanning, Information Systems Security, Secure Coding, Security Controls, Software Design Patterns

      4
      Rating, 4 out of 5 stars
      ·
      579 reviews

      Intermediate · Specialization · 3 - 6 Months

    • 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

    • F

      Fundação Instituto de Administração

      Data & Finance for the future

      Skills you'll gain: Financial Statement Analysis, Financial Statements, Financial Analysis, Business Analytics, Regression Analysis, Business Valuation, Descriptive Statistics, Data Analysis, Data-Driven Decision-Making, Statistical Inference, Financial Accounting, Cash Flows, Balance Sheet, Income Statement, Competitive Analysis, International Finance, Business Economics, Economics, Market Dynamics, Business Planning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      447 reviews

      Intermediate · Specialization · 3 - 6 Months

    • C

      Coursera Project Network

      Introduction to HTML

      Skills you'll gain: Hypertext Markup Language (HTML), Front-End Web Development, Web Design and Development, Web Development, Web Development Tools, Web Applications, Web Content, Integrated Development Environments

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.1K reviews

      Beginner · Guided Project · Less Than 2 Hours

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…394041…263

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

    • Machine Learning: Clustering & Retrieval: University of Washington
    • Data Processing Using Python: Nanjing University
    • Market Research: Queen Mary University of London
    • Introduction to Time Value of Money (TVM): University of Michigan
    • Advanced Models for Decision Making: University of Minnesota
    • Understanding the Enterprise Systems Environment: SAP
    • Customer Relationship Management: Starweaver
    • Microsoft Front-End Developer: Microsoft
    • Fundamentals of Computer Network Security: University of Colorado System
    • Use Canva to Design Digital Course Collateral: Coursera Project Network

    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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