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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 Lausanne

      Challenging Forensic Science: How Science Should Speak to Court

      Skills you'll gain: Criminal Investigation and Forensics, Legal Proceedings, Scientific Methods, Statistical Analysis, Report Writing, Probability & Statistics, Research, Technical Communication, Verification And Validation, Ethical Standards And Conduct

      4.9
      Rating, 4.9 out of 5 stars
      ·
      510 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      Y

      Yonsei University

      Emerging Technologies: From Smartphones to IoT to Big Data

      Skills you'll gain: Apache Spark, Augmented Reality, Cloud Computing Architecture, Big Data, Wireless Networks, SPSS, Augmented and Virtual Reality (AR/VR), Cloud Computing, Cloud Services, Internet Of Things, Live Streaming, Analytics, Real Time Data, Apache Hadoop, Telecommunications, Multimedia, Emerging Technologies, Mobile Development, Apple iOS, Display Devices

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Algorithms for Searching, Sorting, and Indexing

      Skills you'll gain: Data Structures, Algorithms, Pseudocode, Computational Thinking, Programming Principles, Analysis, Big Data, Probability & Statistics

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      493 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Machine Learning in the Enterprise

      Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Data Management, Data Governance, Workflow Management, Applied Machine Learning, Data Pipelines, Machine Learning, Predictive Modeling, Feature Engineering, Continuous Monitoring

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.5K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Digital Health

      Skills you'll gain: Health Technology, Data Visualization Software, Telehealth, Agile Methodology, Health Disparities, Health Informatics, Health Care, Health Care Procedure and Regulation, Health Systems, Electronic Medical Record, Health Information Management, Interoperability, Public Health, Epidemiology, Tableau Software, Digital Transformation, User Centered Design, Technology Strategies, Big Data, Analytics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      288 reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Supervised Machine Learning: Classification

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Applied Machine Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Data Processing, Data Cleansing, Machine Learning, Regression Analysis, Data Manipulation, Business Analytics, Feature Engineering, Random Forest Algorithm, Statistical Modeling, Sampling (Statistics), Performance Metric

      4.8
      Rating, 4.8 out of 5 stars
      ·
      411 reviews

      Intermediate · Course · 1 - 3 Months

    • N

      National Taiwan University

      機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

      Skills you'll gain: Supervised Learning, Machine Learning, Classification And Regression Tree (CART), Theoretical Computer Science, Applied Mathematics, Mathematical Modeling, Probability & Statistics, Regression Analysis, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      932 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Apply Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Data Ethics, Computer Vision, Deep Learning, Applied Machine Learning, Machine Learning, Unsupervised Learning, Information Privacy, Artificial Intelligence

      4.8
      Rating, 4.8 out of 5 stars
      ·
      545 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      E

      ESSEC Business School

      Foundations of strategic business analytics

      Skills you'll gain: Business Analytics, Forecasting, Data Presentation, Predictive Analytics, R Programming, Information Technology, Statistical Analysis, Communication, Business Strategy, Business, Statistics, Data Analysis, Data Visualization, Regression Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      655 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Illinois Urbana-Champaign

      Investments I: Fundamentals of Performance Evaluation

      Skills you'll gain: Investments, Finance, Portfolio Management, Business Valuation, Financial Modeling, Equities, Return On Investment, Financial Analysis, Asset Management, Microsoft Excel, Regression Analysis, Risk Analysis, Performance Analysis, Estimation, Cash Flows

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      914 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      COVID19 Data Analysis Using Python

      Skills you'll gain: Correlation Analysis, Seaborn, Data Cleansing, Data Visualization, Statistical Analysis, Data Manipulation, Data Analysis, Exploratory Data Analysis, Pandas (Python Package), Data Integration, Infectious Diseases

      4.5
      Rating, 4.5 out of 5 stars
      ·
      2K reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Equivalent Circuit Cell Model Simulation

      Skills you'll gain: Simulations, Mathematical Modeling, Electrical Engineering, Matlab, Engineering Calculations, Electrical Systems, Laboratory Testing, Applied Mathematics, Scripting, Data Analysis Software

      4.7
      Rating, 4.7 out of 5 stars
      ·
      547 reviews

      Intermediate · Course · 1 - 3 Months

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    1…373839…197

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

    • Challenging Forensic Science: How Science Should Speak to Court: University of Lausanne
    • Emerging Technologies: From Smartphones to IoT to Big Data: Yonsei University
    • Algorithms for Searching, Sorting, and Indexing: University of Colorado Boulder
    • Machine Learning in the Enterprise: Google Cloud
    • Digital Health: Imperial College London
    • Supervised Machine Learning: Classification: IBM
    • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
    • Apply Generative Adversarial Networks (GANs): DeepLearning.AI
    • Foundations of strategic business analytics: ESSEC Business School
    • Investments I: Fundamentals of Performance Evaluation: University of Illinois Urbana-Champaign

    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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