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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

    • G

      Google Cloud

      Machine Learning in the Enterprise - 한국어

      Skills you'll gain: Data Management, MLOps (Machine Learning Operations), Data Governance, Data Processing, Workflow Management, Google Cloud Platform, Applied Machine Learning, Data Pipelines, Predictive Modeling, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Continuous Monitoring, Containerization

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Encoder-Decoder Architecture - 日本語版

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Applied Machine Learning, Machine Learning Methods, Deep Learning, Natural Language Processing, Machine Learning

      Advanced · Course · 1 - 4 Weeks

    • Status: New
      New
      G

      Google Cloud

      Introduction to AI and Machine Learning on GC - Deutsch

      Skills you'll gain: Generative AI, Google Cloud Platform, MLOps (Machine Learning Operations), Cloud Development, Artificial Intelligence and Machine Learning (AI/ML), Natural Language Processing, Applied Machine Learning, Large Language Modeling, Artificial Intelligence, Machine Learning, Cloud Infrastructure, Predictive Modeling

      Beginner · Course · 1 - 3 Months

    • G

      Google Cloud

      Launching into Machine Learning - Italiano

      Skills you'll gain: Applied Machine Learning, Data Quality, Machine Learning Methods, Machine Learning, Data Cleansing, Machine Learning Algorithms, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Google Cloud Platform, Exploratory Data Analysis, Predictive Modeling, Performance Tuning, Big Data, Sampling (Statistics), Regression Analysis

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      P

      Politecnico di Milano

      Le Derivate: come si calcolano

      Skills you'll gain: Calculus, Applied Mathematics, Derivatives, Algebra, Mathematical Theory & Analysis, Geometry, Graphical Tools, Graphing

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Attention Mechanism - Deutsch

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

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Geliştiriciler İçin Sorumlu Yapay Zeka

      Skills you'll gain: Cloud Security, Generative AI, Data Ethics, Information Privacy, Google Cloud Platform, Artificial Intelligence, Data Security, Information Systems Security, Testability, Maintainability, Open Source Technology, Safety and Security, Artificial Intelligence and Machine Learning (AI/ML), Data Visualization Software, Applied Machine Learning, Machine Learning, Software Documentation, Data Validation, Data Quality, Data Analysis

      Intermediate · Specialization · 1 - 3 Months

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - Español

      Skills you'll gain: Generative AI, Workflow Management, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Jupyter, Google Cloud Platform, SQL, Applied Machine Learning, Customer Relationship Management, Query Languages

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Applying Machine Learning to Your Data with GC - Español

      Skills you'll gain: Google Cloud Platform, Applied Machine Learning, Machine Learning, Big Data, Predictive Modeling, Deep Learning, Artificial Intelligence, Natural Language Processing, Computer Vision, Application Programming Interface (API)

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      NLP – Embeddings & Text Preprocessing in Python

      Skills you'll gain: Natural Language Processing, Text Mining, Data Processing, Applied Machine Learning, Data Transformation, Unstructured Data, Feature Engineering, Machine Learning Algorithms, Computer Programming

      Intermediate · Course · 1 - 3 Months

    • U

      University of Maryland, College Park

      Digital Marketing 2

      Skills you'll gain: Pay Per Click Advertising, Marketing Analytics, Search Engine Optimization, Analytics, Big Data, Google Analytics, Digital Marketing, Search Engine Marketing, Paid media, Web Analytics, Web Analytics and SEO, Online Advertising, Digital Advertising, Marketing Effectiveness, A/B Testing, Applied Machine Learning, Marketing Automation, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML)

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      P

      Packt

      Introduction to Website Development Technologies

      Skills you'll gain: Hypertext Markup Language (HTML), Web Development, Bootstrap (Front-End Framework), Development Environment, Responsive Web Design, Version Control, GitHub, Cascading Style Sheets (CSS), Web Design, Front-End Web Development, Application Deployment, Javascript, Integrated Development Environments, Web Development Tools, Cloud Hosting

      Beginner · Course · 1 - 3 Months

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

    • Machine Learning in the Enterprise - 한국어: Google Cloud
    • Encoder-Decoder Architecture - 日本語版: Google Cloud
    • Introduction to AI and Machine Learning on GC - Deutsch: Google Cloud
    • Launching into Machine Learning - Italiano: Google Cloud
    • Le Derivate: come si calcolano: Politecnico di Milano
    • Attention Mechanism - Deutsch: Google Cloud
    • Geliştiriciler İçin Sorumlu Yapay Zeka: Google Cloud
    • Work with Gemini Models in BigQuery - Español: Google Cloud
    • Applying Machine Learning to Your Data with GC - Español: Google Cloud
    • NLP – Embeddings & Text Preprocessing in Python: Packt

    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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