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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
      L

      LearnQuest

      Teradata: Building Analytics Systems

      Skills you'll gain: Exploratory Data Analysis, Teradata SQL, JSON, Data Integration, Advanced Analytics, Data Cleansing, Text Mining, Data Quality, Data Analysis, Statistical Analysis, Application Programming Interface (API), Natural Language Processing

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Exploring and Preparing Your Data with BigQuery - Español

      Skills you'll gain: Data Cleansing, Data Transformation, Big Data, Google Cloud Platform, Data Quality, Data Analysis, SQL, Exploratory Data Analysis, Databases, Cloud Platforms, Data Visualization Software

      Beginner · Course · 1 - 3 Months

    • G

      Google Cloud

      Attention Mechanism - 繁體中文

      Skills you'll gain: Machine Learning Methods, Artificial Neural Networks, Deep Learning, Natural Language Processing, Applied Machine Learning, Text Mining

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Attention Mechanism - Bahasa Indonesia

      Skills you'll gain: Machine Learning Methods, Performance Tuning, Applied Machine Learning, Natural Language Processing, Artificial Neural Networks, Deep Learning

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      G

      Google Cloud

      Using BigQuery Machine Learning for inference

      Skills you'll gain: Data Analysis, Big Data, Applied Machine Learning, Google Cloud Platform, Machine Learning Algorithms, Machine Learning

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Nouvelles approches pour mesurer la santé de la population

      Skills you'll gain: Survey Creation, Epidemiology, Data Collection, Public Health, Health Equity, Health Policy, Sampling (Statistics), Health Informatics, Health Disparities, Health Information Management, Data Integration, Continuous Monitoring

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Introduction to Image Generation - Português Brasileiro

      Skills you'll gain: Generative AI, Image Analysis, Google Cloud Platform, Deep Learning, Unsupervised Learning, Machine Learning Methods, Applied Machine Learning

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Instructor Network

      GenAI for Customer Analytics and Insights with JUNE

      Skills you'll gain: Product Improvement, Customer Insights, Customer Analysis, Generative AI, Customer Data Management, Marketing Analytics, Web Analytics, Analytics, Management Reporting, Product Management, Data Analysis, Data Collection, Dashboard, Performance Metric

      Intermediate · Course · 1 - 4 Weeks

    • H

      H2O.ai

      H2O Driverless AI Starter Course

      Skills you'll gain: Data Processing, Predictive Modeling, Feature Engineering, MLOps (Machine Learning Operations), Artificial Intelligence and Machine Learning (AI/ML), Data Manipulation, Exploratory Data Analysis, Data Analysis, Machine Learning, Supervised Learning, Interactive Data Visualization, Data Import/Export

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Creating Derived Tables Using LookML

      Skills you'll gain: Looker (Software), Database Development, Database Design, Data Modeling, SQL, Exploratory Data Analysis

      Beginner · Project · Less Than 2 Hours

    • J

      Johns Hopkins University

      تحليل البيانات الاستكشافية

      Skills you'll gain: Exploratory Data Analysis, R Programming, Ggplot2, Statistical Methods, Data Analysis, Statistical Analysis, Unsupervised Learning, Histogram, Dimensionality Reduction, Heat Maps, Color Theory

      Mixed · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Последовательные модели

      Skills you'll gain: Deep Learning, Natural Language Processing, Tensorflow, PyTorch (Machine Learning Library), Applied Machine Learning, Artificial Neural Networks

      Intermediate · Course · 1 - 4 Weeks

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

    • Teradata: Building Analytics Systems: LearnQuest
    • Exploring and Preparing Your Data with BigQuery - Español: Google Cloud
    • Attention Mechanism - 繁體中文: Google Cloud
    • Attention Mechanism - Bahasa Indonesia: Google Cloud
    • Using BigQuery Machine Learning for inference: Google Cloud
    • Nouvelles approches pour mesurer la santé de la population: Johns Hopkins University
    • Introduction to Image Generation - Português Brasileiro: Google Cloud
    • GenAI for Customer Analytics and Insights with JUNE: Coursera Instructor Network
    • H2O Driverless AI Starter Course: H2O.ai
    • Creating Derived Tables Using LookML: Google Cloud

    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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