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    Results for "applied statistics"

    • Google Cloud

      Art and Science of Machine Learning en Español

      Skills you'll gain: Tensorflow, Performance Tuning, Artificial Neural Networks, Deep Learning, Applied Machine Learning, Supervised Learning, Machine Learning, Machine Learning Algorithms, Regression Analysis, Google Cloud Platform

      4.7
      Rating, 4.7 out of 5 stars
      ·
      51 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free
      Free

      Coursera Instructor Network

      Introduction to Generative AI in Legal

      Skills you'll gain: Legal Strategy, Legal Research, Generative AI, Legal Risk, Case Law, Regulation and Legal Compliance, Legal Proceedings, Artificial Intelligence, Legal Writing, Document Management, ChatGPT, Ethical Standards And Conduct, Automation, Natural Language Processing, Client Services

      5
      Rating, 5 out of 5 stars
      ·
      7 reviews

      Beginner · Course · 1 - 3 Months

    • Johns Hopkins University

      Calculus through Data & Modelling: Vector Calculus

      Skills you'll gain: Integral Calculus, Calculus, Linear Algebra, Mathematical Theory & Analysis, Advanced Mathematics, Visualization (Computer Graphics), Applied Mathematics, Graphing, Mathematical Modeling, Spatial Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      43 reviews

      Intermediate · Course · 1 - 4 Weeks

    • University of Glasgow

      Generative Pre-trained Transformers (GPT)

      Skills you'll gain: Large Language Modeling, ChatGPT, Generative AI, Natural Language Processing, PyTorch (Machine Learning Library), Risk Management Framework, Prompt Engineering, Tensorflow, Data Ethics, Deep Learning, Artificial Neural Networks, Artificial Intelligence

      4.4
      Rating, 4.4 out of 5 stars
      ·
      31 reviews

      Intermediate · Course · 1 - 4 Weeks

    • EIT Digital

      Basic Recommender Systems

      Skills you'll gain: Data Ethics, Usability, System Requirements, Machine Learning Algorithms, Innovation, Algorithms, Predictive Modeling, Data-Driven Decision-Making, Data Mining, Applied Machine Learning, Statistical Methods, Performance Tuning

      4.3
      Rating, 4.3 out of 5 stars
      ·
      43 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free

      Coursera Instructor Network

      GenAI for Business Intelligence Analysts

      Skills you'll gain: Business Intelligence, Generative AI, Business Analytics, Business Process Automation, Data-Driven Decision-Making, Data Ethics, Data Storytelling, Advanced Analytics, Exploratory Data Analysis, Large Language Modeling, Data Governance, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 4 Weeks

    • University of California, Davis

      Python Basics for Online Research

      Skills you'll gain: Debugging, Jupyter, Computational Thinking, Web Scraping, Python Programming, Programming Principles, Data Manipulation, Data Access, Text Mining, Application Programming Interface (API), Scripting, Computer Programming, Program Development, Data Cleansing, Automation, Algorithms, Probability & Statistics, Data Structures, Data Analysis, Visualization (Computer Graphics)

      3.3
      Rating, 3.3 out of 5 stars
      ·
      28 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New

      Johns Hopkins University

      Introduction to Uncertainty Quantification

      Skills you'll gain: Probability, Bayesian Statistics, Probability Distribution, Risk Modeling, Mathematical Modeling, Statistical Inference, Markov Model, Reliability, Simulations, Applied Mathematics, Statistical Analysis, Regression Analysis

      Intermediate · Course · 1 - 4 Weeks

    • University of Colorado Boulder

      Ethical Issues in Data Science

      Skills you'll gain: Data Ethics, Healthcare Ethics, Ethical Standards And Conduct, Data Security, Data Science, Medical Privacy, Machine Learning, Algorithms, Information Privacy, Artificial Intelligence, Diversity Awareness, Cybersecurity

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      41 reviews

      Beginner · Course · 1 - 3 Months

    • Coursera Project Network

      Adobe Illustrator for Beginners: Creative Brand System

      Skills you'll gain: Adobe Illustrator, Logo Design, Graphic Design, Adobe Creative Cloud, Graphic and Visual Design, Digital Design, Typography, Design Elements And Principles, File Management, Color Theory

      4.1
      Rating, 4.1 out of 5 stars
      ·
      7 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: New
      New

      Dubai College of Tourism

      Introduction to Restaurant Revenue Management

      Skills you'll gain: Revenue Management, Restaurant Operation, Forecasting, Key Performance Indicators (KPIs), Hospitality Management, Customer Demand Planning, Trend Analysis, Performance Analysis, Financial Forecasting, Team Management, Price Negotiation, Performance Measurement, Data-Driven Decision-Making, Business Strategies

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New

      Microsoft

      Building Powerful Reports and Dashboards in Power BI

      Skills you'll gain: Data Ethics, Dashboard, Power BI, Business Intelligence, Interactive Data Visualization, Data Presentation, Data Storytelling, Data Visualization Software, Data-Driven Decision-Making, Business Reporting, Data Analysis Expressions (DAX), Data Security, Key Performance Indicators (KPIs), Data Analysis, Performance Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      7 reviews

      Beginner · Course · 1 - 3 Months

    Searches related to applied statistics

    applied statistics for data analytics
    applied statistics and probability
    statistics and applied data analysis
    1…114115116…197

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

    • Art and Science of Machine Learning en Español: Google Cloud
    • Introduction to Generative AI in Legal: Coursera Instructor Network
    • Calculus through Data & Modelling: Vector Calculus: Johns Hopkins University
    • Generative Pre-trained Transformers (GPT): University of Glasgow
    • Basic Recommender Systems: EIT Digital
    • GenAI for Business Intelligence Analysts: Coursera Instructor Network
    • Python Basics for Online Research: University of California, Davis
    • Introduction to Uncertainty Quantification: Johns Hopkins University
    • Ethical Issues in Data Science: University of Colorado Boulder
    • Adobe Illustrator for Beginners: Creative Brand System: Coursera Project Network

    Frequently Asked Questions about Applied Statistics

    Applied statistics is the use of statistical techniques to solve real-world data analysis problems. In contrast to the pure study of mathematical statistics, applied statistics is typically used by and for non-mathematicians in fields ranging from social science to business. Indeed, in the big data era, applied statistics has become important for deriving insights and guiding decision-making in virtually every industry.

    The increased reliance on data and statistics to help understand our world has made the careful application of these techniques even more essential; too often, statistics can be used erroneously or even misleadingly when methods of analysis are not properly connected to research questions. Thus, a major aspect of applied statistics is the accurate communication of findings for a non-technical audience, including specifics about data sources, relevance to the problem at hand, and degrees of uncertainty.

    That said, the statistical approaches used in this field are the same as in the study of mathematical statistics. Rigorous use of statistical hypothesis testing, statistical inference, linear regression techniques, and analysis of variance (ANOVA) are core to the work of applied statistics. And, as in other areas of data science, Python programming and R programming are often used to analyze large datasets when Microsoft Excel is not sufficiently powerful.‎

    Demand for data-driven insights is growing fast across all fields, making a background in applied statistics the gateway to a wide variety of careers. Financial institutions and companies of all kinds rely on business analytics to guide investments and operations; political candidates and advocacy groups need to conduct surveys and understand public polling data to understand popular opinion on today’s issues; and even sports teams are increasingly hiring experts in applied statistics to make decisions regarding personnel as well as in-game strategy.

    While many jobs in applied statistics may require only a bachelor’s degree in fields such as mathematics or computer science, high-level roles often expect a master’s degree in statistics. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160 as of May 2019, and these jobs are expected to grow much faster than average due to the need to analyze fast-growing volumes of electronic data.‎

    Yes, with absolute certainty. Coursera offers courses and Specializations in applied statistics for business, social science, and other areas, as well as related topics such as data science and Python programming. These courses are offered by top-ranked universities and leading companies from around the world, including the University of Michigan, the University of Amsterdam, and the University of Virginia, and IBM. Regardless of whether you’re a student looking to learn more about this exciting field or a mid-career professional upgrading their skill set, the combination of a high-quality education and the flexibility of learning online makes Coursera a great choice.‎

    It's very helpful to have strong math skills, analytical skills, and experience solving problems before starting to learn applied statistics. It's also good to have experience and a good comfort level with technology and computers. Previous experience in statistics is also helpful, although not required. You may also benefit from having prior experience using Excel spreadsheets as you begin to learn applied statistics.‎

    People best suited for roles in applied statistics are analytical thinkers. They enjoy problem-solving by taking available data and analyzing it to arrive at solutions. They also have effective communication skills so that information can flow clearly to all stakeholders within an organization. Organization and multitasking come easily to people best suited for roles in applied statistics because these individuals need to deal with large amounts of information and manage their time and resources efficiently. People well suited for these roles also pay close attention to detail to make sure the outcomes they're tasked with delivering meet or exceed expectations.‎

    While the use of applied statistics can be found in almost every industry, learning applied statistics may be especially interesting to you if you're seeking a career in the insurance, web analytics, or energy sectors. These are some of the top industries that currently utilize applied statistics. However, a person in any position in which data is gathered and analyzed to create solutions, innovations, or improvements would benefit from learning applied statistics, from coaches and hospital administrators to bloggers, data scientists, and bankers. If you would like to know how to ensure you're collecting the right data, how to analyze data correctly, and how to effectively report your findings so they can be applied in real-world situations, learning applied statistics may be right for you.‎

    Online Applied Statistics courses offer a convenient and flexible way to enhance your existing knowledge or learn new Applied Statistics skills. With a wide range of Applied Statistics classes, you can conveniently learn at your own pace to advance your Applied Statistics career skills.‎

    When looking to enhance your workforce's skills in Applied Statistics, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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