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    • Applied Statistics

    Applied Statistics Courses Online

    Understand applied statistics for data analysis and interpretation. Learn statistical methods and tools for various industries.

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    Explore the Applied Statistics Course Catalog

    • U

      University of Colorado Boulder

      Object-Oriented Analysis and Design: Foundations & Concepts

      Skills you'll gain: Object Oriented Design, Unified Modeling Language, Object Oriented Programming (OOP), Test Driven Development (TDD), JUnit, Java, Unit Testing, Software Testing, Software Design Patterns, Software Design, Systems Analysis, Conceptual Design

      Build toward a degree

      4.2
      Rating, 4.2 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Data Visualization using dplyr and ggplot2 in R

      Skills you'll gain: Ggplot2, Tidyverse (R Package), Data Analysis, Exploratory Data Analysis, R Programming, Data Visualization Software, Data Wrangling, Data Manipulation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      18 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      L

      LearnQuest

      AI 알고리즘 모델과 한계점

      Skills you'll gain: Predictive Modeling, Predictive Analytics, Machine Learning Algorithms, Machine Learning, Algorithms, Data Ethics, Statistical Modeling, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Applied Machine Learning, Business Ethics, Ethical Standards And Conduct

      4.3
      Rating, 4.3 out of 5 stars
      ·
      14 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      U

      University of Michigan

      NumPy and Pandas Basics for Future Data Scientists

      Skills you'll gain: NumPy, Pandas (Python Package), Debugging, Data Manipulation, Python Programming, Data Cleansing, Data Structures, Descriptive Statistics

      Intermediate · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Gestion de l’analyse des données

      Skills you'll gain: Data Analysis, Analytical Skills, Data Management, Exploratory Data Analysis, Data-Driven Decision-Making, Predictive Analytics, Data Presentation, Descriptive Analytics, Data Collection, Statistical Modeling, Data Validation, Statistical Inference, Communication

      4.4
      Rating, 4.4 out of 5 stars
      ·
      9 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      PyCaret: Anatomy of Regression

      Skills you'll gain: Regression Analysis, Statistical Modeling, Predictive Modeling, Scikit Learn (Machine Learning Library), Feature Engineering, Data Manipulation, Pandas (Python Package), Machine Learning Methods, Data Visualization, Exploratory Data Analysis, Performance Tuning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      14 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • F

      Fractal Analytics

      Advanced Machine Learning Algorithms

      Skills you'll gain: Feature Engineering, Machine Learning Algorithms, Random Forest Algorithm, Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Classification And Regression Tree (CART), Supervised Learning, Predictive Modeling, Decision Tree Learning, Performance Tuning, Regression Analysis

      3.6
      Rating, 3.6 out of 5 stars
      ·
      8 reviews

      Beginner · Course · 1 - 3 Months

    • F

      Fundação Instituto de Administração

      Análise de Dados Quantitativos

      Skills you'll gain: Quantitative Research, Marketing Analytics, Market Analysis, Market Research, Exploratory Data Analysis, Strategic Marketing, Forecasting, Strategic Decision-Making, Data Analysis, Predictive Modeling, Customer Analysis, Statistical Modeling, Statistical Analysis, Correlation Analysis, Regression Analysis, Unsupervised Learning, Variance Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      23 reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Explore and Create Reports with Data Studio

      Skills you'll gain: Exploratory Data Analysis, Data Visualization Software, Dashboard, Interactive Data Visualization, Data Analysis, Data Integration

      4.4
      Rating, 4.4 out of 5 stars
      ·
      20 reviews

      Beginner · Project · Less Than 2 Hours

    • K

      Korea Advanced Institute of Science and Technology(KAIST)

      Differential Equations Part II Series Solutions

      Skills you'll gain: Differential Equations, Applied Mathematics, Advanced Mathematics, Calculus, Linear Algebra, Engineering Analysis, Mathematical Theory & Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11 reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      J

      Johns Hopkins University

      Foundations of Neural Networks

      Skills you'll gain: Data Ethics, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Reinforcement Learning, Generative AI, Debugging, Artificial Intelligence, Unsupervised Learning, Machine Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Ethical Standards And Conduct, Applied Machine Learning, Unstructured Data, Linear Algebra, Markov Model, Data-Driven Decision-Making, Natural Language Processing

      Intermediate · Specialization · 3 - 6 Months

    • U

      Universidad de los Andes

      Desarrollo y Diseño de Videojuegos: Proyecto final

      Skills you'll gain: Game Design, Video Game Development, Agile Methodology, Agile Software Development, Software Design Documents, Software Development Methodologies, Augmented and Virtual Reality (AR/VR), Virtual Reality, Sprint Planning, Video Production, Technical Documentation, Prototyping, Digital Publishing, User Interface (UI)

      5
      Rating, 5 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 3 Months

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    1…138139140…197

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

    • Object-Oriented Analysis and Design: Foundations & Concepts: University of Colorado Boulder
    • Data Visualization using dplyr and ggplot2 in R: Coursera Project Network
    • AI 알고리즘 모델과 한계점: LearnQuest
    • NumPy and Pandas Basics for Future Data Scientists: University of Michigan
    • Gestion de l’analyse des données: Johns Hopkins University
    • PyCaret: Anatomy of Regression: Coursera Project Network
    • Advanced Machine Learning Algorithms: Fractal Analytics
    • Análise de Dados Quantitativos: Fundação Instituto de Administração
    • Explore and Create Reports with Data Studio: Google Cloud
    • Differential Equations Part II Series Solutions: Korea Advanced Institute of Science and Technology(KAIST)

    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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