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    Results for "advanced statistics"

    • E

      ESSEC Business School

      Foundations of strategic business analytics

      Skills you'll gain: Business Analytics, Forecasting, Data Presentation, Predictive Analytics, R Programming, Information Technology, Statistical Analysis, Communication, Business Strategy, Business, Statistics, Data Analysis, Data Visualization, Regression Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      654 reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Introduction to High-Performance and Parallel Computing

      Skills you'll gain: Bash (Scripting Language), Scalability, Distributed Computing, Computer Systems, Big Data, Operating Systems, Performance Tuning, File Systems, Linux, Command-Line Interface, Programming Principles, OS Process Management

      Build toward a degree

      3.6
      Rating, 3.6 out of 5 stars
      ·
      137 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Real-Time Embedded Systems

      Skills you'll gain: Real-Time Operating Systems, Embedded Systems, Reliability, Performance Tuning, Embedded Software, Systems Architecture, Hardware Architecture, Software Architecture, Verification And Validation, Software Design, Debugging, System Design and Implementation, Hardware Design, Linux, System Programming, Software Systems, Performance Testing, Software Documentation, Testability, OS Process Management

      Build toward a degree

      3.9
      Rating, 3.9 out of 5 stars
      ·
      105 reviews

      Intermediate · Specialization · 3 - 6 Months

    • M

      Meta

      React Native

      Skills you'll gain: React Native, Mobile Development, Cross Platform Development, UI Components, Mobile Development Tools, iOS Development, React.js, Front-End Web Development, Android Development, User Interface (UI), Development Environment

      4.8
      Rating, 4.8 out of 5 stars
      ·
      364 reviews

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Computer Vision Fundamentals with Google Cloud

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Applied Machine Learning, Artificial Neural Networks, Deep Learning, Supervised Learning, Google Cloud Platform, Machine Learning Methods, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Small Data, Data Processing, Cloud API

      4.5
      Rating, 4.5 out of 5 stars
      ·
      543 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Global Trends for Business and Society

      Skills you'll gain: Demography, Market Trend, Trend Analysis, International Relations, Socioeconomics, Social Sciences, Systems Thinking, Cultural Diversity, Financial Systems, World History, Economics, Business Economics, Governance

      4.8
      Rating, 4.8 out of 5 stars
      ·
      919 reviews

      Mixed · Course · 1 - 4 Weeks

    • W

      Wesleyan University

      Data Management and Visualization

      Skills you'll gain: Descriptive Statistics, Data Manipulation, Data Presentation, Data Management, Data Literacy, Graphing, SAS (Software), Peer Review, Data Analysis, Statistics, Research Reports, Exploratory Data Analysis, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      937 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Create Charts and Dashboards Using Microsoft Excel

      Skills you'll gain: Dashboard, Microsoft Excel, Microsoft 365, Spreadsheet Software, Data Visualization, Trend Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      918 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • I

      IBM

      Relational Database Administration (DBA)

      Skills you'll gain: Database Management, Database Architecture and Administration, Relational Databases, Operational Databases, Database Systems, IBM DB2, MySQL, Performance Tuning, PostgreSQL, Disaster Recovery, Data Storage Technologies, Database Design, System Monitoring, Role-Based Access Control (RBAC), User Accounts, Encryption

      4.4
      Rating, 4.4 out of 5 stars
      ·
      235 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California, Irvine

      E-Marketing

      Skills you'll gain: Pay Per Click Advertising, Search Engine Marketing, Customer Retention, Persona Development, Digital Marketing, Marketing Analytics, Search Engine Optimization, Key Performance Indicators (KPIs), Target Audience, Keyword Research, Social Media Strategy, Marketing Effectiveness, Customer Acquisition Management, Customer experience improvement, Marketing Strategy and Techniques, Customer Engagement, A/B Testing, Web Analytics, Marketing Strategies, Google Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      385 reviews

      Beginner · Specialization · 1 - 3 Months

    • M

      Microsoft

      Microsoft Generative AI for Data Analysis

      Skills you'll gain: Prompt Engineering, Data Storytelling, Data Presentation, Dashboard, Interactive Data Visualization, Generative AI, Data Ethics, Data Visualization, Infographics, Anomaly Detection, Excel Formulas, Predictive Modeling, Data Visualization Software, Microsoft Copilot, Business Reporting, Risk Analysis, Text Mining, Risk Management, Data Quality, Data Pipelines

      4.3
      Rating, 4.3 out of 5 stars
      ·
      60 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • D

      DeepLearning.AI

      Generative Deep Learning with TensorFlow

      Skills you'll gain: Generative AI, Tensorflow, Image Analysis, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Computer Graphics, Unsupervised Learning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      305 reviews

      Intermediate · Course · 1 - 4 Weeks

    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…444546…263

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

    • Foundations of strategic business analytics: ESSEC Business School
    • Introduction to High-Performance and Parallel Computing: University of Colorado Boulder
    • Real-Time Embedded Systems: University of Colorado Boulder
    • React Native: Meta
    • Computer Vision Fundamentals with Google Cloud: Google Cloud
    • Global Trends for Business and Society: University of Pennsylvania
    • Data Management and Visualization: Wesleyan University
    • Create Charts and Dashboards Using Microsoft Excel: Coursera Project Network
    • Relational Database Administration (DBA): IBM
    • E-Marketing: University of California, Irvine

    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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