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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

    • Status: New
      New
      Status: Free Trial
      Free Trial
      D

      Dartmouth College

      Predictive Analytics

      Skills you'll gain: Business Ethics, Predictive Analytics, Scikit Learn (Machine Learning Library), Digital Transformation, Data-Driven Decision-Making, Feature Engineering, Applied Machine Learning, Statistical Machine Learning, Classification And Regression Tree (CART), Regression Analysis, Python Programming, Cloud Computing, Data Quality, Performance Metric, Artificial Neural Networks

      Intermediate · Course · 1 - 3 Months

    • U

      University of Maryland, College Park

      Program Management Fundamentals: Driving Strategic Change

      Skills you'll gain: Stakeholder Engagement, Program Management, Change Management, Stakeholder Communications, Strategic Leadership, Product Roadmaps, Leadership, Organizational Change, Organizational Strategy, Project Management Office (PMO), Project Management, Innovation, Digital Transformation, Decision Making

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      데이터 중심 기업을 위한 비즈니스 지표

      Skills you'll gain: Business Metrics, Business Analytics, Analytics, Business Intelligence, Tableau Software, Cash Flows, Big Data, Performance Measurement, Key Performance Indicators (KPIs), Spreadsheet Software, Data Analysis, Data-Driven Decision-Making, Web Analytics, Market Share, E-Commerce

      Mixed · Course · 1 - 3 Months

    • G

      Google Cloud

      Orchestrating a TFX Pipeline with Airflow

      Skills you'll gain: Apache Airflow, Tensorflow, MLOps (Machine Learning Operations), Google Cloud Platform, Data Pipelines, Machine Learning Methods, Applied Machine Learning

      1.3
      Rating, 1.3 out of 5 stars
      ·
      6 reviews

      Beginner · Project · Less Than 2 Hours

    • J

      Johns Hopkins University

      Random Processes

      Skills you'll gain: Probability & Statistics, Probability Distribution, Simulations, Statistical Modeling, Estimation, Correlation Analysis, Engineering Analysis, Statistical Analysis, Reliability, Engineering, Spatial Analysis

      Mixed · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Machine/Deep Learning for Mining Quality Prediction-Enhanced

      Skills you'll gain: Exploratory Data Analysis, Regression Analysis, Predictive Modeling, Applied Machine Learning, Data Manipulation, Data Analysis, Random Forest Algorithm, Decision Tree Learning, Machine Learning Algorithms, Data Visualization Software, Artificial Neural Networks, Deep Learning, Statistical Methods

      Beginner · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      TensorFlow for Beginners: Basic Binary Image Classification

      Skills you'll gain: Tensorflow, Image Analysis, Artificial Neural Networks, Application Deployment, Data Processing, Applied Machine Learning, Computer Vision, Deep Learning

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      U

      Universidad Nacional Autónoma de México

      Python: de usuario a explorador de datos

      Skills you'll gain: Matplotlib, NumPy, Extract, Transform, Load, Time Series Analysis and Forecasting, Plot (Graphics), Pandas (Python Package), Exploratory Data Analysis, Data Science, Data Visualization Software, Data Analysis, Statistical Analysis, Scatter Plots, Graphing, Data Import/Export, Data Manipulation, Python Programming, Linear Algebra, File Management

      Beginner · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Advanced Reproducibility in Cancer Informatics

      Skills you'll gain: Code Review, GitHub, Git (Version Control System), Version Control, Docker (Software), Software Development Tools, Containerization, Bioinformatics, Health Informatics, Automation, Science and Research, Medical Science and Research, Technical Communication

      Advanced · Course · 1 - 3 Months

    • D

      Duke University

      R을 사용한 확률 및 데이터 소개

      Skills you'll gain: Exploratory Data Analysis, Sampling (Statistics), Probability Distribution, R Programming, Bayesian Statistics, Data Analysis, Probability, Statistics, Statistical Analysis, Descriptive Statistics, Statistical Inference

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      B

      Board Infinity

      Agile Development Excellence: Scrum, User Story, CI Insight

      Skills you'll gain: Scaled Agile Framework, Continuous Integration, Sprint Planning, Scrum (Software Development), Kanban Principles, CI/CD, Sprint Retrospectives, Lean Methodologies, Continuous Improvement Process, Collaborative Software, Agile Methodology, Continuous Delivery, Team Building, Test Automation, Agile Project Management, Jenkins, Continuous Deployment, Agile Software Development, Cross-Functional Collaboration, DevOps

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Advanced Capstone Spacecraft Dynamics and Control Project

      Skills you'll gain: Vibrations, Control Systems, Mechanics, Torque (Physics), Mechanical Engineering, Engineering Analysis, Engineering Calculations, Differential Equations, Mathematical Modeling, Simulation and Simulation Software

      Advanced · Course · 1 - 4 Weeks

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    1…162163164…199

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

    • Predictive Analytics: Dartmouth College
    • Program Management Fundamentals: Driving Strategic Change: University of Maryland, College Park
    • 데이터 중심 기업을 위한 비즈니스 지표: Duke University
    • Orchestrating a TFX Pipeline with Airflow: Google Cloud
    • Random Processes: Johns Hopkins University
    • Machine/Deep Learning for Mining Quality Prediction-Enhanced: Coursera Project Network
    • TensorFlow for Beginners: Basic Binary Image Classification: Coursera Project Network
    • Python: de usuario a explorador de datos: Universidad Nacional Autónoma de México
    • Advanced Reproducibility in Cancer Informatics: Johns Hopkins University
    • R을 사용한 확률 및 데이터 소개: Duke University

    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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