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    Results for "advanced statistics"

    • D

      Duke University

      Inferential Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Reporting, Statistical Methods, R Programming, Statistical Software, Statistical Analysis, Probability & Statistics, Data Literacy, Sampling (Statistics), Probability Distribution, Software Installation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      I

      IBM

      IBM Relational Database Administrator

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, Database Administration, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Transformation, Data Store, IBM DB2, Jupyter, Generative AI

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • V

      Vanderbilt University

      Generative AI Automation

      Skills you'll gain: Prompt Engineering, ChatGPT, Ideation, Verification And Validation, Data Validation, Data Presentation, Productivity, Generative AI, Document Management, Data Synthesis, Image Analysis, Data Capture, Artificial Intelligence, OpenAI, Large Language Modeling, Data Analysis, Organizational Skills, Risk Management Framework, Computer Vision, Microsoft Excel

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • D
      S

      Multiple educators

      Machine Learning

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), Artificial Intelligence, NumPy, Predictive Modeling, Deep Learning, Reinforcement Learning, Random Forest Algorithm, Feature Engineering

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      33K reviews

      Beginner · Specialization · 1 - 3 Months

    • I

      IBM

      IBM Business Analyst

      Skills you'll gain: Data Storytelling, Requirements Elicitation, Risk Mitigation, Business Analysis, Business Process Modeling, Risk Analysis, Process Mapping, Process Optimization, Requirements Management, Risk Management, Business Requirements, Stakeholder Management, Work Breakdown Structure, Scope Management, Process Analysis, Stakeholder Engagement, Data Visualization Software, Excel Formulas, Microsoft Excel, Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      V

      Vanderbilt University

      AI Agents and Agentic AI in Python: Powered by Generative AI

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI Agents, OpenAI, Productivity, Python Programming, Agentic systems, Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Artificial Intelligence, Large Language Modeling, Creative Thinking, Ingenuity, Brainstorming, Software Development Tools, Application Development, Prototyping, Persona (User Experience), Business Logic, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.8K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      University of Pennsylvania

      English for Career Development

      Skills you'll gain: English Language, Vocabulary, Business Writing, Interviewing Skills, Verbal Communication Skills, Business Correspondence, Social Skills, Professional Networking, Professional Development, Business Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      16K reviews

      Mixed · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Mathematics for Machine Learning and Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Python Programming, Jupyter, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.7K reviews

      Intermediate · Specialization · 1 - 3 Months

    • M

      Meta

      Advanced MySQL Topics

      Skills you'll gain: MySQL, Database Management, Stored Procedure, Database Development, SQL, Performance Tuning, Relational Databases, Query Languages, JSON, Analytics, Data Analysis, Transaction Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      234 reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      Macquarie University

      Excel Skills for Business

      Skills you'll gain: Microsoft Excel, Dashboard, Excel Formulas, Spreadsheet Software, Data Visualization, Excel Macros, Data Validation, Data Analysis Expressions (DAX), Data Cleansing, Data Modeling, Financial Forecasting, Predictive Modeling, Financial Modeling, Workflow Management, Finance, Data Management, Business Intelligence Software, Consolidation, Data Integrity, Data Entry

      4.9
      Rating, 4.9 out of 5 stars
      ·
      62K reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      Microsoft

      Work Smarter with Microsoft Excel

      Skills you'll gain: Microsoft Excel, Excel Formulas, Data Visualization, Spreadsheet Software, Microsoft 365, Productivity Software, Data Import/Export, Data Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.8K reviews

      Beginner · Course · 1 - 3 Months

    • P

      PwC

      Data Visualization with Advanced Excel

      Skills you'll gain: Data Presentation, Dashboard, Data Storytelling, Data Visualization Software, Microsoft Excel, Spreadsheet Software, Excel Formulas, Graphing, Pivot Tables And Charts, Data Modeling, Databases, Data Analysis, Simulation and Simulation Software

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3K reviews

      Beginner · Course · 1 - 4 Weeks

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…456…264

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

    • Inferential Statistics: Duke University
    • IBM Relational Database Administrator: IBM
    • Generative AI Automation: Vanderbilt University
    • Machine Learning: DeepLearning.AI
    • IBM Business Analyst: IBM
    • AI Agents and Agentic AI in Python: Powered by Generative AI: Vanderbilt University
    • English for Career Development: University of Pennsylvania
    • Mathematics for Machine Learning and Data Science: DeepLearning.AI
    • Advanced MySQL Topics: Meta
    • Excel Skills for Business: Macquarie 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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