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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

    • D

      DeepLearning.AI

      TensorFlow: Advanced Techniques

      Skills you'll gain: Generative AI, Tensorflow, Computer Vision, Image Analysis, Deep Learning, Keras (Neural Network Library), Applied Machine Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Feature Engineering, Distributed Computing, Computer Graphics, Unsupervised Learning, Network Model, Visualization (Computer Graphics), Network Architecture, Performance Tuning, Machine Learning Methods, API Design, Object Oriented Programming (OOP)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Financial Planning for Young Adults

      Skills you'll gain: Financial Planning, Investments, Budgeting, Risk Management, Goal Setting, Loans, Finance, Insurance, Credit Risk

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 3 Months

    • N

      Northwestern University

      Modern Robotics: Mechanics, Planning, and Control

      Skills you'll gain: Machine Controls, Control Systems, Mathematical Modeling, Simulation and Simulation Software, Automation Engineering, Engineering Calculations, Engineering, Mechanics, Mechanical Engineering, Torque (Physics), Artificial Intelligence, Applied Mathematics, Engineering Analysis, Automation, Computational Logic, Virtual Environment, Robotic Process Automation, Graph Theory, Matlab, Numerical Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of London

      International Business Essentials

      Skills you'll gain: Financial Statements, Business Planning, Sampling (Statistics), Leadership and Management, Descriptive Statistics, Team Management, Team Building, Organizational Structure, Data Presentation, Professional Networking, Communication, Organizational Change, Business Mathematics, Business Strategy, Professionalism, Resource Allocation, Competitive Analysis, Linear Algebra, Mathematical Modeling, Business Strategies

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      U

      University of Colorado Boulder

      Statistics and Applied Data Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Statistical Analysis, Regression Analysis, Statistical Programming, Probability, Probability Distribution, Sampling (Statistics), Box Plots, Histogram, R Programming, Statistical Methods, Scatter Plots, Microsoft Excel, Probability & Statistics, Statistics, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      33 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      Skills you'll gain: Statistical Inference, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, R Programming, Data Ethics, Statistical Methods, Data Analysis, Statistical Analysis, Data Modeling, Predictive Modeling, Probability & Statistics, Advanced Analytics, Correlation Analysis, Forecasting, Data Science, A/B Testing, Machine Learning, Classification And Regression Tree (CART), Linear Algebra

      Build toward a degree

      4.1
      Rating, 4.1 out of 5 stars
      ·
      52 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      University of Washington

      Computational Neuroscience

      Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Mathematical Modeling, Biology, Linear Algebra, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Minnesota

      Agile Software Development

      Skills you'll gain: User Story, Agile Software Development, Agile Methodology, Agile Project Management, Scrum (Software Development), Sprint Planning, Software Development Methodologies, Sprint Retrospectives, Waterfall Methodology, Continuous Integration, Test Driven Development (TDD)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.4K reviews

      Intermediate · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      A Crash Course in Data Science

      Skills you'll gain: Data Science, Data Management, Data-Driven Decision-Making, Project Design, Performance Metric, Software Engineering, Machine Learning, Predictive Modeling, Statistical Inference

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.3K reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Simple Regression Analysis in Public Health

      Skills you'll gain: Biostatistics, Regression Analysis, Statistical Methods, Statistical Analysis, Epidemiology, Quantitative Research, Public Health, Data Analysis, Probability & Statistics, Statistical Inference

      4.7
      Rating, 4.7 out of 5 stars
      ·
      382 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Alberta

      Introduction to Software Product Management

      Skills you'll gain: Agile Software Development, Software Development, Product Requirements, Requirements Management, Product Management, Software Engineering, Project Planning, Process Development, Project Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.7K reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      Institute for the Future

      Futures Thinking

      Skills you'll gain: Forecasting, Visionary, Proactivity, Innovation, Strategic Thinking, Creative Thinking, Action Oriented, Simulations, Optimism, Planning, Community Organizing, Systems Thinking, Virtual Reality, Trend Analysis, Empathy, Market Trend, Game Theory, Cognitive flexibility, Storytelling, Personal Development

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

      Beginner · Specialization · 3 - 6 Months

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    1…181920…198

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

    • TensorFlow: Advanced Techniques: DeepLearning.AI
    • Financial Planning for Young Adults: University of Illinois Urbana-Champaign
    • Modern Robotics: Mechanics, Planning, and Control: Northwestern University
    • International Business Essentials: University of London
    • Statistics and Applied Data Analysis: University of Colorado Boulder
    • Statistical Modeling for Data Science Applications: University of Colorado Boulder
    • Computational Neuroscience: University of Washington
    • Agile Software Development: University of Minnesota
    • A Crash Course in Data Science: Johns Hopkins University
    • Simple Regression Analysis in Public Health : Johns Hopkins 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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