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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: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Social Computing

      Skills you'll gain: Network Analysis, Graph Theory, Machine Learning, Applied Machine Learning, Social Sciences, Statistical Analysis, Amazon Web Services, R Programming, Tensorflow, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Research Design, Sociology, Human Machine Interfaces, Data Collection, Machine Learning Methods, Behavioral Economics, Analytics, Natural Language Processing, Game Design

      4.2
      Rating, 4.2 out of 5 stars
      ·
      8 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Using Generative AI for Learning Design Activities

      Skills you'll gain: Generative AI, Prompt Engineering, Persona Development, Artificial Intelligence, Ideation, ChatGPT

      4.9
      Rating, 4.9 out of 5 stars
      ·
      15 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Build a Budget and Analyze Variance using Google Sheets

      Skills you'll gain: Google Sheets, Variance Analysis, Trend Analysis, Budget Management, Budgeting, Spreadsheet Software, Presentations, Financial Statements

      4.6
      Rating, 4.6 out of 5 stars
      ·
      78 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      L

      LearnQuest

      Capstone Project: Advanced AI for Drug Discovery

      Skills you'll gain: Feature Engineering, Bioinformatics, Dimensionality Reduction, Predictive Modeling, Artificial Neural Networks, Pandas (Python Package), Verification And Validation, Unsupervised Learning, Scikit Learn (Machine Learning Library), Data Manipulation, Regression Analysis, Machine Learning Algorithms, Exploratory Data Analysis

      2.1
      Rating, 2.1 out of 5 stars
      ·
      16 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Build your first Machine Learning Pipeline using Dataiku

      Skills you'll gain: Data Import/Export, Exploratory Data Analysis, Predictive Modeling, Applied Machine Learning, Data Pipelines, Data Manipulation, Data Analysis, Time Series Analysis and Forecasting

      4.5
      Rating, 4.5 out of 5 stars
      ·
      58 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • U

      University of California, Davis

      SQL für Data Science

      Skills you'll gain: Data Governance, SQL, Data Quality, Data Manipulation, Database Design, Data Transformation, Query Languages, Data Modeling, Databases, Relational Databases, Data Analysis, Descriptive Statistics

      4.3
      Rating, 4.3 out of 5 stars
      ·
      29 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      L

      LearnQuest

      5G Network Architecture and Protocols

      Skills you'll gain: Network Architecture, Network Protocols, Wireless Networks, Network Performance Management, Network Planning And Design, Computer Networking, Telecommunications, Emerging Technologies, Digital Communications

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      L

      L&T EduTech

      Industrial Fluid systems & Smart Factory Automation

      Skills you'll gain: Electrical Systems, Automation Engineering, Hydraulics, Programmable Logic Controllers, Control Systems, Mechanical Engineering, Real Time Data, Internet Of Things, Automation, Industrial Engineering, Hardware Troubleshooting, Equipment Design, Manufacturing Processes, Manufacturing and Production, Production Process, Robotic Process Automation, Failure Analysis, Emerging Technologies, Digital Transformation, Manufacturing Operations

      4.5
      Rating, 4.5 out of 5 stars
      ·
      21 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      How Google does Machine Learning 日本語版

      Skills you'll gain: Google Cloud Platform, Tensorflow, Machine Learning, Big Data, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Deep Learning, Data Ethics, Natural Language Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      132 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Amsterdam

      Try RRI! A guide for Responsible Research and Innovation

      Skills you'll gain: Science and Research, Research, Experimentation, Risk Management, Innovation, Policty Analysis, Research, and Development, Stakeholder Engagement, Governance, Collaboration, Planning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      8 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Design of High-Performance Optical Systems

      Skills you'll gain: Engineering, Scientific, and Technical Instruments, Image Analysis, Laboratory Equipment, Systems Design, Human Factors, Engineering Calculations, Technical Design, Simulation and Simulation Software, Engineering Design Process, Mathematical Modeling, Applied Mathematics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      49 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Geneva

      Global Statistics - Composite Indices for International Comparisons

      Skills you'll gain: Data Synthesis, Analytical Skills, International Relations, Economic Development, Statistics, Economics, Market Opportunities, Data Analysis, Labor Compliance, Social Studies, Data Quality, Transportation Operations

      4.6
      Rating, 4.6 out of 5 stars
      ·
      49 reviews

      Intermediate · Course · 1 - 3 Months

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    1…107108109…199

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

    • Social Computing: Johns Hopkins University
    • Using Generative AI for Learning Design Activities : University of Michigan
    • Build a Budget and Analyze Variance using Google Sheets: Coursera Project Network
    • Capstone Project: Advanced AI for Drug Discovery: LearnQuest
    • Build your first Machine Learning Pipeline using Dataiku : Coursera Project Network
    • SQL für Data Science: University of California, Davis
    • 5G Network Architecture and Protocols: LearnQuest
    • Industrial Fluid systems & Smart Factory Automation: L&T EduTech
    • How Google does Machine Learning 日本語版: Google Cloud
    • Try RRI! A guide for Responsible Research and Innovation: University of Amsterdam

    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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