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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

    • I

      IIT Roorkee

      Data Mining for Smart Cities

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Anomaly Detection, Data Mining, Machine Learning Algorithms, Data Processing, Big Data, Data Cleansing, Data Visualization, Python Programming, Data-Driven Decision-Making, NumPy, Exploratory Data Analysis, Deep Learning, Regression Analysis, Artificial Neural Networks

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      K

      Korea Advanced Institute of Science and Technology(KAIST)

      Math for AI Beginner Part 2 : Vector Calulus

      Skills you'll gain: Integral Calculus, Applied Mathematics, Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Calculus, Mathematics and Mathematical Modeling, Mathematical Modeling, Advanced Mathematics, Machine Learning

      Beginner · Course · 1 - 3 Months

    • P

      Packt

      Recommender Systems Complete Course Beginner to Advanced

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Natural Language Processing, Deep Learning, Predictive Modeling, Applied Machine Learning, Time Series Analysis and Forecasting, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Attention Mechanism - Français

      Skills you'll gain: Machine Learning Methods, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Natural Language Processing

      Intermediate · Course · 1 - 4 Weeks

    • I

      IE Business School

      Competitive Interactions and Disruptive Change

      Skills you'll gain: Market Dynamics, Competitive Analysis, Market Trend, Market Share, Trend Analysis, Market Analysis, Market Intelligence, Business Economics, Strategic Marketing, Business Strategies, Strategic Thinking, Benchmarking

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      P

      Packt

      RNN Architecture and Sentiment Classification

      Skills you'll gain: PyTorch (Machine Learning Library), Text Mining, Artificial Neural Networks, Natural Language Processing, Deep Learning, Applied Machine Learning, Network Architecture, Time Series Analysis and Forecasting, Machine Learning Algorithms, Data Processing

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Employing Best Practices for Improving the Usability of LookML Projects

      Skills you'll gain: Looker (Software), Maintainability, Usability Testing, Exploratory Data Analysis, Data Dictionary, Data Literacy

      Intermediate · Project · Less Than 2 Hours

    • Status: New
      New
      C

      Coursera Instructor Network

      Smart Data Cleaning with Generative AI

      Skills you'll gain: Data Quality, Data Ethics, Data Cleansing, Generative AI, Data Validation, Automation, Applied Machine Learning, Data Transformation, Tensorflow, Pandas (Python Package), OpenAI, Artificial Intelligence, Jupyter, Alteryx

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Introduction to Vertex Forecasting and Time Series in Practice

      Skills you'll gain: MLOps (Machine Learning Operations), Time Series Analysis and Forecasting, Google Cloud Platform, Forecasting, Feature Engineering, Data Transformation, Predictive Modeling, Data Cleansing, Applied Machine Learning, Continuous Monitoring, Artificial Intelligence and Machine Learning (AI/ML)

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      P

      Packt

      Deep Learning with Keras and Practical Applications

      Skills you'll gain: Keras (Neural Network Library), Image Analysis, Exploratory Data Analysis, Deep Learning, Data Processing, Artificial Neural Networks, Computer Vision, Applied Machine Learning, Predictive Modeling, Data Import/Export, Pandas (Python Package), Classification And Regression Tree (CART), Matplotlib, Performance Tuning

      Intermediate · Course · 3 - 6 Months

    • G

      Google Cloud

      Machine Learning in the Enterprise - Español

      Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Data Pipelines, Applied Machine Learning, Data Processing, Machine Learning, Feature Engineering, Data Management, Performance Tuning, Continuous Monitoring

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      Financial Analysis with ARIMA and Time Series Forecasting

      Skills you'll gain: Time Series Analysis and Forecasting, Financial Forecasting, Statistical Analysis, Machine Learning, Trend Analysis, Financial Data, Financial Modeling, Jupyter, Predictive Modeling, Regression Analysis, Finance, GitHub

      Intermediate · Course · 1 - 3 Months

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

    • Data Mining for Smart Cities: IIT Roorkee
    • Math for AI Beginner Part 2 : Vector Calulus: Korea Advanced Institute of Science and Technology(KAIST)
    • Recommender Systems Complete Course Beginner to Advanced: Packt
    • Attention Mechanism - Français: Google Cloud
    • Competitive Interactions and Disruptive Change: IE Business School
    • RNN Architecture and Sentiment Classification: Packt
    • Employing Best Practices for Improving the Usability of LookML Projects: Google Cloud
    • Smart Data Cleaning with Generative AI: Coursera Instructor Network
    • Introduction to Vertex Forecasting and Time Series in Practice: Google Cloud
    • Deep Learning with Keras and Practical Applications: 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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