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    Results for "advanced statistics"

    • Status: Free Trial
      Free Trial

      Queen Mary University of London

      Analysis and Interpretation of Data

      Skills you'll gain: Data Analysis, Statistical Analysis, Correlation Analysis, Quantitative Research, Regression Analysis, Content Performance Analysis, Marketing Analytics, Probability & Statistics, Trend Analysis, Data Cleansing, Digital Marketing, Exploratory Data Analysis, Market Research, Return On Investment

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11 reviews

      Beginner · Course · 1 - 4 Weeks

    • Korea Advanced Institute of Science and Technology(KAIST)

      Math for AI beginner part 1 Linear Algebra

      Skills you'll gain: Linear Algebra, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Applied Mathematics, Deep Learning, Machine Learning, Supervised Learning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      30 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      L&T EduTech

      Geospatial Technology for Construction

      Skills you'll gain: Geospatial Mapping, Geospatial Information and Technology, Geographic Information Systems, Construction, Construction Management, Architecture and Construction, Civil and Architectural Engineering, Spatial Analysis, Global Positioning Systems, GIS Software, As-Built Drawings, Survey Creation, Engineering, Scientific, and Technical Instruments, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      Tsinghua University

      Data Structures and Algorithms

      Skills you'll gain: Data Structures, Algorithms, Graph Theory, Computational Thinking, Programming Principles, Theoretical Computer Science, Database Design, Query Languages, Spatial Analysis, System Design and Implementation, Computational Logic, Computer Programming

      2.8
      Rating, 2.8 out of 5 stars
      ·
      39 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Pontificia Universidad Católica de Chile

      Python para Ciencia de Datos

      Skills you'll gain: Descriptive Analytics, Data-Driven Decision-Making, Data Analysis, Data Visualization Software, Predictive Analytics, Business Analytics, Database Management, Data Science, Relational Databases, Data Processing, Trend Analysis, Forecasting, Data Manipulation, Python Programming

      3.8
      Rating, 3.8 out of 5 stars
      ·
      67 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      IE Business School

      Riesgos y oportunidades empresariales en una economía globalizada

      Skills you'll gain: Economics, Financial Policy, Economic Development, Trend Analysis, Global Marketing, Business Economics, International Relations, Analysis, Socioeconomics, Business Risk Management, Public Policies, Business Strategies, World History, Investments

      4.9
      Rating, 4.9 out of 5 stars
      ·
      102 reviews

      Intermediate · Course · 1 - 3 Months

    • Coursera Instructor Network

      GIS Mastery: Spatial Data, Remote Sensing, Decision Support

      Skills you'll gain: Geographic Information Systems, Geospatial Information and Technology, Geospatial Mapping, Spatial Data Analysis, Spatial Analysis, Global Positioning Systems

      4.5
      Rating, 4.5 out of 5 stars
      ·
      12 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial

      Microsoft

      Blazor for Front-End Development

      Skills you'll gain: Microsoft Copilot, User Interface and User Experience (UI/UX) Design, UI Components, Performance Tuning, Front-End Web Development, Event-Driven Programming, Web Applications, Server Side, Data Validation, Debugging

      4.5
      Rating, 4.5 out of 5 stars
      ·
      12 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      Universidad de los Andes

      Plataformas para procesar datos no tradicionales​

      Skills you'll gain: Spatial Analysis, NoSQL, Spatial Data Analysis, Geospatial Mapping, Geographic Information Systems, Public Cloud, Big Data, MongoDB, Apache Hadoop, Apache Spark, Distributed Computing, Data Architecture, Cloud Services, Data Processing, Cloud Computing, Scalability, Databases, Environmental Monitoring, File Systems, Image Analysis

      4.2
      Rating, 4.2 out of 5 stars
      ·
      10 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial

      Johns Hopkins University

      Precalculus: Mathematical Modeling

      Skills you'll gain: Data Analysis, Applied Mathematics, Mathematical Modeling, Analytical Skills, Statistics, Systems Of Measurement, Correlation Analysis, Regression Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      89 reviews

      Beginner · Course · 1 - 4 Weeks

    • Coursera Project Network

      Using Descriptive Statistics to Analyze Data in R

      Skills you'll gain: Descriptive Statistics, R Programming, Statistical Reporting, Data Quality, Data Cleansing, Statistical Methods, Data Manipulation, Data Import/Export

      4.6
      Rating, 4.6 out of 5 stars
      ·
      92 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial

      Northeastern University

      Business Application of Machine Learning and Artificial Intelligence in Healthcare

      Skills you'll gain: Health Informatics, Decision Support Systems, Business Intelligence, Business Analytics, Business Process Automation, Predictive Analytics, Data-Driven Decision-Making, Customer experience strategy (CX), Advanced Analytics, Artificial Intelligence and Machine Learning (AI/ML), Process Analysis, Predictive Modeling, Applied Machine Learning, Healthcare Industry Knowledge, Emerging Technologies

      4.4
      Rating, 4.4 out of 5 stars
      ·
      81 reviews

      Intermediate · Course · 1 - 4 Weeks

    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

    • Analysis and Interpretation of Data: Queen Mary University of London
    • Math for AI beginner part 1 Linear Algebra: Korea Advanced Institute of Science and Technology(KAIST)
    • Geospatial Technology for Construction : L&T EduTech
    • Data Structures and Algorithms: Tsinghua University
    • Python para Ciencia de Datos: Pontificia Universidad Católica de Chile
    • Riesgos y oportunidades empresariales en una economía globalizada: IE Business School
    • GIS Mastery: Spatial Data, Remote Sensing, Decision Support: Coursera Instructor Network
    • Blazor for Front-End Development: Microsoft
    • Plataformas para procesar datos no tradicionales​: Universidad de los Andes
    • Precalculus: Mathematical Modeling: 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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