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    Results for "advanced statistics"

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      Ludwig-Maximilians-Universität München (LMU)

      Advanced Competitive Strategy

      Skills you'll gain: Mergers & Acquisitions, Customer Retention, Business Strategy, Growth Strategies, Compliance Management, Competitive Analysis, Strategic Partnership, Product Strategy, New Business Development, Market Dynamics, Market Analysis

      4.7
      Rating, 4.7 out of 5 stars
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      874 reviews

      Mixed · Course · 1 - 3 Months

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      Michigan State University

      Photography Techniques: Light, Content, and Sharing

      Skills you'll gain: Photography, Photo Editing, Peer Review, Color Theory, Storytelling, Creativity, Information Privacy, Web Design and Development

      4.8
      Rating, 4.8 out of 5 stars
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      1.1K reviews

      Mixed · Course · 1 - 4 Weeks

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      Yonsei University

      Emerging Technologies: From Smartphones to IoT to Big Data

      Skills you'll gain: Apache Spark, Augmented Reality, Cloud Computing Architecture, Big Data, Wireless Networks, SPSS, Augmented and Virtual Reality (AR/VR), Cloud Computing, Cloud Services, Internet Of Things, Live Streaming, Analytics, Real Time Data, Apache Hadoop, Telecommunications, Multimedia, Emerging Technologies, Mobile Development, Apple iOS, Display Devices

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      MathWorks

      Image Processing for Engineering and Science

      Skills you'll gain: Image Analysis, Matlab, Computer Vision, Automation, Anomaly Detection, Spatial Data Analysis, Medical Imaging, Spatial Analysis, Quantitative Research, Graphical Tools, Data Access, Data Import/Export, Data Store

      4.8
      Rating, 4.8 out of 5 stars
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      210 reviews

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      Starweaver

      Customer Relationship Management

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      Rating, 4.6 out of 5 stars
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      Beginner · Course · 1 - 4 Weeks

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      Board Infinity

      Quality Improvement and Management

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      227 reviews

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      University of Illinois Urbana-Champaign

      Text Retrieval and Search Engines

      Skills you'll gain: Text Mining, Natural Language Processing, Data Mining, Unstructured Data, Big Data, Web Analytics and SEO, Machine Learning, Information Architecture, Statistical Methods, Algorithms, Probability & Statistics

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      960 reviews

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      DeepLearning.AI

      Data Analytics Foundations

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      4.7
      Rating, 4.7 out of 5 stars
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      83 reviews

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      University of Toronto

      Visual Perception for Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Computer Graphics, Artificial Neural Networks, Visualization (Computer Graphics), Artificial Intelligence and Machine Learning (AI/ML), Python Programming, Linear Algebra

      4.7
      Rating, 4.7 out of 5 stars
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      581 reviews

      Advanced · Course · 1 - 3 Months

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      IBM

      Supervised Machine Learning: Classification

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Applied Machine Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Data Processing, Data Cleansing, Machine Learning, Regression Analysis, Data Manipulation, Business Analytics, Feature Engineering, Random Forest Algorithm, Statistical Modeling, Sampling (Statistics), Performance Metric

      4.8
      Rating, 4.8 out of 5 stars
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      411 reviews

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      University of Illinois Urbana-Champaign

      Investments I: Fundamentals of Performance Evaluation

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      4.7
      Rating, 4.7 out of 5 stars
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      914 reviews

      Intermediate · Course · 1 - 3 Months

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      Johns Hopkins University

      Data Science in Real Life

      Skills you'll gain: Data Quality, Data Management, Technical Communication, Data Analysis, Data-Driven Decision-Making, Statistical Analysis, Data Science, Statistical Machine Learning, Statistical Inference, A/B Testing, Statistical Modeling

      4.5
      Rating, 4.5 out of 5 stars
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      2.4K reviews

      Mixed · Course · 1 - 4 Weeks

    Searches related to advanced statistics

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

    • Advanced Competitive Strategy: Ludwig-Maximilians-Universität München (LMU)
    • Photography Techniques: Light, Content, and Sharing: Michigan State University
    • Emerging Technologies: From Smartphones to IoT to Big Data: Yonsei University
    • Image Processing for Engineering and Science: MathWorks
    • Customer Relationship Management: Starweaver
    • Quality Improvement and Management: Board Infinity
    • Text Retrieval and Search Engines: University of Illinois Urbana-Champaign
    • Data Analytics Foundations: DeepLearning.AI
    • Visual Perception for Self-Driving Cars: University of Toronto
    • Supervised Machine Learning: Classification: IBM

    Frequently Asked Questions about Advanced Statistics

    Advanced statistics are the mathematical tools used to discover and explore complex relationships between different variables in large datasets. In contrast to basic statistics such as average and analysis of variance (ANOVA) that simply describe the characteristics of a dataset, advanced statistical approaches often seek to make predictions about the world. This requires the use of more sophisticated statistical inference tools, such as generalized linear models for regression analysis capable of establishing how multiple interrelated factors may impact projected outcomes.

    These advanced statistical methods are increasingly important in the field of data science, which is tasked with uncovering important business insights and developing predictive models from diverse big data-scale datasets. These techniques are also especially important for the proper training and use of machine learning algorithms. As in data science and machine learning more generally, R programming and Python programming skills are typically relied upon to conduct these advanced statistical analyses.‎

    Advanced statistics skills are essential for work in data science, machine learning, and artificial intelligence (AI), as statistical approaches are at the heart of the learning algorithms that make these applications possible. An understanding of statistics is likewise important for professionals in finance, healthcare, and other industries that are increasingly making use of machine learning and AI, as they increasingly need to work closely with data scientists to ensure that these powerful techniques are developed to solve the right business problems.

    Those wishing to delve deeper into advanced statistical methods and help develop new mathematical approaches in the field may pursue a master’s or even a PhD in statistics. These experts work in academia, government, or at private sector companies involved in scientific or engineering research. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160, and this specialized career path is expected to be in high demand due to expanding opportunities to use statistics to navigate our data-rich world.‎

    Certainly. Coursera offers a variety of courses in advanced statistics as well as their applications in the context of fields like data science and machine learning. In fact, coursework in statistics is often a prerequisite for data science classes. Regardless of your level of expertise and needs in these areas, Coursera enables you to learn remotely from top-ranked schools like the University of Michigan, Johns Hopkins University, and Duke University. And, since you can view course materials and complete coursework on a flexible schedule, there’s an exceedingly high probability that you can fit online learning about advanced statistics into your existing school or work life.‎

    You need to have strong math skills, especially in basic calculus, linear algebra, and statistics before starting to learn advanced statistics. It's important that you have strong technical skills and are very comfortable on the computer, strong analytical skills, and the ability to carefully examine and question data that is presented to you so that you can organize and draw conclusions from it. For learning some concepts in advanced statistics, you'll need to have experience using the R statistical software package and understand Bayesian estimation, principles of maximum-likelihood estimation, and calculus-based probability.‎

    People who enjoy mathematics are best suited for roles in advanced statistics, especially those who enjoy concepts like probability, linear models, and statistics and how they relate to data science. They can quickly grasp and apply complex technical concepts as well. Those who enjoy testing hypotheses and figuring out uncertain outcomes based on probability are also well suited for roles in advanced statistics. Also, people who have wide-ranging computer skills, the ability to communicate their statistical findings in plain language, problem-solving and analytical skills, and teamwork and collaborative skills are best suited for roles involving advanced statistics.‎

    If you're aspiring to be a biostatistician or data scientist, learning advanced statistics is probably right for you. If you're interested in machine learning and the development of data products, you may also find learning advanced statistics is right for you. People who want to have a career as a statistician, statistical epidemiologist, sports analyst, actuary, market researcher, or investment analyst may also find learning advanced statistics to be the right choice. And if you need to understand how to transform complex sets of data into practical applications, learning advanced statistics is right for you.‎

    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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