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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
      U

      University of Geneva

      Portfolio and Risk Management

      Skills you'll gain: Portfolio Management, Risk Management, Business Risk Management, Investment Management, Risk Analysis, Investments, Asset Management, Wealth Management, Financial Market, Finance, Probability Distribution, Market Dynamics, Correlation Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Introduction to Trading, Machine Learning & GCP

      Skills you'll gain: Machine Learning, Google Cloud Platform, Applied Machine Learning, Supervised Learning, Time Series Analysis and Forecasting, Financial Trading, Deep Learning, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Securities Trading, Technical Analysis, Financial Forecasting, Quantitative Research, Financial Modeling, Forecasting, Regression Analysis

      4
      Rating, 4 out of 5 stars
      ·
      874 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Data Analyst Capstone Project

      Skills you'll gain: Dashboard, Exploratory Data Analysis, Data Wrangling, Statistical Analysis, Data Cleansing, IBM Cognos Analytics, Data Manipulation, Data Collection, Data Presentation, Data Analysis, Web Scraping, Data Storytelling, Box Plots, Pandas (Python Package), Scatter Plots, Histogram

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      P

      Politecnico di Milano

      Artificial Intelligence: an Overview

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Algorithms, Machine Learning, Applied Machine Learning, Intellectual Property, Ethical Standards And Conduct, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Legal Risk, Artificial Intelligence, Reinforcement Learning, General Data Protection Regulation (GDPR), Dimensionality Reduction, Governance, Cloud Platforms, Deep Learning, Law, Regulation, and Compliance, Computer Science, Computer Vision

      4.6
      Rating, 4.6 out of 5 stars
      ·
      612 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Google Advanced Data Analytics Capstone

      Skills you'll gain: Regression Analysis, Data Visualization, Statistical Analysis, Advanced Analytics, Data Analysis, Business Analytics, Data-Driven Decision-Making, Predictive Modeling, Machine Learning Methods, Interviewing Skills, Portfolio Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Washington

      Practical Predictive Analytics: Models and Methods

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Statistical Machine Learning, Predictive Analytics, Advanced Analytics, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Big Data

      4.1
      Rating, 4.1 out of 5 stars
      ·
      320 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Azure Data Scientist Associate (DP-100) Exam Prep

      Skills you'll gain: Databricks, Unsupervised Learning, PySpark, Microsoft Azure, Apache Spark, Scikit Learn (Machine Learning Library), MLOps (Machine Learning Operations), PyTorch (Machine Learning Library), Exploratory Data Analysis, Deep Learning, Data Visualization, Applied Machine Learning, Regression Analysis, Data Science, Predictive Modeling, Jupyter, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Classification And Regression Tree (CART), Cloud Computing

      4.2
      Rating, 4.2 out of 5 stars
      ·
      546 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      W

      Wesleyan University

      Abnormal Psychology

      Skills you'll gain: Motivational Interviewing, Psychological Evaluations, Mental Health Diseases and Disorders, Mental Health Therapies, Behavioral Health, Mental and Behavioral Health, Psychiatry, Psychotherapy, Clinical Psychology, Behavior Management, Psychosocial Assessments, Mental Health, Cultural Diversity, Psychology, Experimentation, Interpersonal Communications, Stress Management, Learning Theory, Goal Setting, Health Disparities

      4.8
      Rating, 4.8 out of 5 stars
      ·
      657 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Linear Regression and Modeling

      Skills you'll gain: Regression Analysis, Data Analysis Software, Statistical Analysis, R Programming, Statistical Modeling, Statistical Inference, Correlation Analysis, Statistical Methods, Exploratory Data Analysis, Mathematical Modeling, Predictive Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Medical Terminology I

      Skills you'll gain: Medical Terminology, Orthopedics, Medical Records, Urology, Anatomy, Electronic Medical Record

      4.9
      Rating, 4.9 out of 5 stars
      ·
      665 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to Neural Networks and PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Deep Learning, Predictive Modeling, Probability & Statistics, Machine Learning, Regression Analysis, Data Manipulation, Linear Algebra

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Build, Train and Deploy ML Models with Keras on Google Cloud

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Data Pipelines, MLOps (Machine Learning Operations), Application Deployment, Deep Learning, Artificial Neural Networks, Data Processing, Scalability, Applied Machine Learning, Machine Learning, Data Transformation

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.8K reviews

      Intermediate · Course · 1 - 3 Months

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    1…262728…197

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

    • Portfolio and Risk Management: University of Geneva
    • Introduction to Trading, Machine Learning & GCP: Google Cloud
    • IBM Data Analyst Capstone Project: IBM
    • Artificial Intelligence: an Overview: Politecnico di Milano
    • Google Advanced Data Analytics Capstone: Google
    • Practical Predictive Analytics: Models and Methods: University of Washington
    • Microsoft Azure Data Scientist Associate (DP-100) Exam Prep: Microsoft
    • Abnormal Psychology: Wesleyan University
    • Linear Regression and Modeling : Duke University
    • Medical Terminology I: Rice 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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