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    Results for "advanced statistics"

    • U

      University of Colorado Boulder

      Business Analytics for Decision Making

      Skills you'll gain: Business Analytics, Risk Analysis, Business Analysis, Decision Making, Analytics, Business Intelligence, Predictive Analytics, Simulation and Simulation Software, Business Modeling, Data Analysis, Process Optimization, Market Analysis, Unsupervised Learning, Microsoft Excel, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.9K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University at Buffalo

      Digital Manufacturing & Design

      Skills you'll gain: Digital Transformation, Manufacturing Processes, Manufacturing Operations, Industrial Engineering, Business Transformation, Digital Design, Data-Driven Decision-Making, Product Lifecycle Management, Supply Chain, Market Dynamics, Safety and Security, Workforce Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Statistical Inference for Estimation in Data Science

      Skills you'll gain: Statistical Inference, Statistical Methods, Probability & Statistics, Statistical Modeling, Sampling (Statistics), Statistical Analysis, Data Science, Probability Distribution

      4.1
      Rating, 4.1 out of 5 stars
      ·
      88 reviews

      Intermediate · Course · 1 - 3 Months

    • L

      Ludwig-Maximilians-Universität München (LMU)

      Advanced Competitive Strategy

      Skills you'll gain: Mergers & Acquisitions, Customer Retention, Business Strategy, Growth Strategies, Compliance Management, Competitive Analysis, Strategic Partnership, Product Strategy, New Business Development, Market Dynamics, Market Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      871 reviews

      Mixed · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Advanced Computer Vision with TensorFlow

      Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Applied Machine Learning, Deep Learning, Feature Engineering, Artificial Neural Networks, Visualization (Computer Graphics), Data Processing, Network Architecture

      4.7
      Rating, 4.7 out of 5 stars
      ·
      520 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      S

      Stanford University

      Game Theory II: Advanced Applications

      Skills you'll gain: Game Theory, Bidding, Social Sciences, Resource Allocation, Political Sciences, Economics, Behavioral Economics, Negotiation, Mathematical Theory & Analysis, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      641 reviews

      Advanced · Course · 1 - 3 Months

    • R

      Rice University

      Business Applications of Hypothesis Testing and Confidence Interval Estimation

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Sample Size Determination, Statistical Inference, Estimation, Statistics, Probability & Statistics, Sampling (Statistics), Statistical Analysis, Microsoft Excel, Excel Formulas, Decision Making

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.3K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Finding Hidden Messages in DNA (Bioinformatics I)

      Skills you'll gain: Bioinformatics, Molecular Biology, Data Analysis, Computational Thinking, Biochemistry, Biology, Life Sciences, Algorithms, Probability & Statistics

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1K reviews

      Intermediate · Course · 1 - 3 Months

    • S

      Starweaver

      Certified Business Analysis Professional™ (CBAP®)

      Skills you'll gain: Process Analysis, Requirements Elicitation, Business Analysis, Risk Analysis, Backlogs, Requirements Management, Stakeholder Engagement, Business Process, User Requirements Documents, User Story, Business Requirements, Requirements Analysis, Business Modeling, Business Process Improvement, Business Risk Management, Business Intelligence, Business Strategies, Financial Analysis, Performance Measurement, Business Planning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      239 reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      MLOps | Machine Learning Operations

      Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Data Ethics, Application Deployment, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, Software Testing, Data Import/Export, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Docker (Software), Rust (Programming Language)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      450 reviews

      Advanced · Specialization · 3 - 6 Months

    • U

      University of Virginia

      Advanced Business Strategy

      Skills you'll gain: Business Strategy, Business Ethics, Corporate Strategy, Competitive Analysis, Strategic Thinking, Stakeholder Management, Innovation, Strategic Planning, International Finance, Business Development, Stakeholder Engagement, Growth Strategies, Strategic Decision-Making, Market Dynamics, Market Opportunities

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

      Beginner · Course · 1 - 4 Weeks

    • I

      ISC2

      Security Principles

      Skills you'll gain: Security Controls, Information Assurance, Cybersecurity, Risk Management Framework, Security Awareness, Cyber Governance, Security Management, Cyber Risk, Security Strategy, Personally Identifiable Information, Data Ethics, Data Integrity

      4.7
      Rating, 4.7 out of 5 stars
      ·
      543 reviews

      Beginner · Course · 1 - 3 Months

    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

    • Business Analytics for Decision Making: University of Colorado Boulder
    • Digital Manufacturing & Design: University at Buffalo
    • Statistical Inference for Estimation in Data Science: University of Colorado Boulder
    • Advanced Competitive Strategy: Ludwig-Maximilians-Universität München (LMU)
    • Advanced Computer Vision with TensorFlow: DeepLearning.AI
    • Game Theory II: Advanced Applications: Stanford University
    • Business Applications of Hypothesis Testing and Confidence Interval Estimation : Rice University
    • Finding Hidden Messages in DNA (Bioinformatics I): University of California San Diego
    • Certified Business Analysis Professionalâ„¢ (CBAP®): Starweaver
    • MLOps | Machine Learning Operations: Duke 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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