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    Results for "advanced statistics"

    • Status: New
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      Microsoft

      Advanced Python Development Techniques

      Skills you'll gain: Data Structures, Generative AI, Test Driven Development (TDD), Integration Testing, Python Programming, Object Oriented Programming (OOP), Cloud Applications, Serverless Computing, Cloud Computing, Microsoft Azure, Algorithms, Software Documentation, Software Development Tools, Maintainability, Code Review, Software Development, Technical Documentation, Application Deployment

      3.8
      Rating, 3.8 out of 5 stars
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      6 reviews

      Beginner · Course · 1 - 3 Months

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      Northeastern University

      Business Application of Machine Learning and Artificial Intelligence in Healthcare

      Skills you'll gain: Health Informatics, Decision Support Systems, Business Intelligence, Business Analytics, Business Process Automation, Predictive Analytics, Data-Driven Decision-Making, Customer experience strategy (CX), Advanced Analytics, Artificial Intelligence and Machine Learning (AI/ML), Process Analysis, Predictive Modeling, Applied Machine Learning, Healthcare Industry Knowledge, Emerging Technologies

      4.4
      Rating, 4.4 out of 5 stars
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      81 reviews

      Intermediate · Course · 1 - 4 Weeks

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      EDUCBA

      ARM Cortex (STM32) Fundamentals: Building Embedded Systems

      Skills you'll gain: Embedded Systems, Embedded Software, C (Programming Language), Programming Principles, Hardware Architecture, Computer Architecture, Debugging, Peripheral Devices

      4.6
      Rating, 4.6 out of 5 stars
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      36 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
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      U

      University of Colorado System

      Data Analysis and Representation, Selection and Iteration

      Skills you'll gain: Computational Thinking, Data Analysis, C (Programming Language), Statistical Analysis, Programming Principles, Data Structures, Descriptive Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      93 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: New
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      University of Maryland, College Park

      Foundations of Digital Marketing

      Skills you'll gain: Search Engine Marketing, Pay Per Click Advertising, Marketing Analytics, Search Engine Optimization, Web Analytics, Web Analytics and SEO, Online Advertising, Data Presentation, Data Visualization, Analytics, Digital Marketing, Keyword Research, Apache Hadoop, Data-Driven Decision-Making, Digital Advertising, Return On Investment, A/B Testing, Advertising, Marketing Automation, Marketing Strategies

      4.5
      Rating, 4.5 out of 5 stars
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      11 reviews

      Beginner · Specialization · 3 - 6 Months

    • K

      Korea Advanced Institute of Science and Technology(KAIST)

      Introduction to Semiconductor Process 2

      Skills you'll gain: Semiconductors, Electronics, Process Engineering, Manufacturing Processes, Production Process, Electronic Components, Process Control, Chemistry

      4.8
      Rating, 4.8 out of 5 stars
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      10 reviews

      Intermediate · Course · 1 - 3 Months

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      LearnQuest

      Security for Blockchain and DApps

      Skills you'll gain: Blockchain, Key Management, Threat Modeling, Application Security, Computer Security, Security Controls, Cryptography, Security Testing, Cybersecurity, Security Requirements Analysis, Data Security, Information Systems Security, Network Security, Security Engineering, Vulnerability Assessments, Encryption, Secure Coding, Cryptographic Protocols, Cyber Security Assessment, Distributed Denial-Of-Service (DDoS) Attacks

      4.6
      Rating, 4.6 out of 5 stars
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      18 reviews

      Intermediate · Specialization · 3 - 6 Months

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      Duke University

      Art of the MOOC: Experiments with Sound

      Skills you'll gain: World Music, Music History, Music, Musical Composition, Music Theory, Multimedia, Public Affairs, Performing Arts, Music Performance, Electronic Media, Liberal Arts, Experimentation, Creativity, Cultural Diversity, Research

      4.8
      Rating, 4.8 out of 5 stars
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      74 reviews

      Beginner · Course · 1 - 3 Months

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      Amazon Web Services

      DevOps and AI on AWS: Upgrading Apps with Generative AI

      Skills you'll gain: Prompt Engineering, Application Deployment, Amazon Elastic Compute Cloud, Unit Testing, Amazon Web Services, Generative AI, Data Ethics, Application Development, DevOps, Large Language Modeling, Git (Version Control System), CI/CD, Artificial Intelligence

      Beginner · Course · 1 - 4 Weeks

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      Packt

      Elasticsearch 8 and the Elastic Stack: In-Depth and Hands-On

      Skills you'll gain: Kibana, Data Import/Export, Restful API, Data Mapping, Data Visualization Software, Data Integration, Query Languages, Time Series Analysis and Forecasting, Dashboard, Data Management, Apache Kafka, Histogram, Information Architecture, NoSQL, Performance Tuning, Software Installation, Amazon Web Services, Security Information and Event Management (SIEM), System Monitoring, Data Maintenance

      4.5
      Rating, 4.5 out of 5 stars
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      11 reviews

      Beginner · Specialization · 1 - 3 Months

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      Google Cloud

      Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs

      Skills you'll gain: Data Warehousing, Google Cloud Platform, Big Data, Apache Spark, Database Management, Data Integration, Dataflow, SQL, Data Pipelines, Metadata Management, Data Management, Real Time Data, Tensorflow, Data Science, Command-Line Interface, Applied Machine Learning, Cloud-Based Integration, Query Languages, Power BI, Data Loss Prevention

      4.3
      Rating, 4.3 out of 5 stars
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      125 reviews

      Intermediate · Specialization · 1 - 3 Months

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      Duke University

      Virtualization, Docker, and Kubernetes for Data Engineering

      Skills you'll gain: Site Reliability Engineering, Docker (Software), Containerization, Kubernetes, Virtualization, Devops Tools, Microservices, Development Environment, Software Development Tools, Application Deployment, Virtual Machines, Software Development, Cloud Development, Database Management, GitHub, Scalability

      3.9
      Rating, 3.9 out of 5 stars
      ·
      39 reviews

      Advanced · 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 Python Development Techniques: Microsoft
    • Business Application of Machine Learning and Artificial Intelligence in Healthcare: Northeastern University
    • ARM Cortex (STM32) Fundamentals: Building Embedded Systems: EDUCBA
    • Data Analysis and Representation, Selection and Iteration: University of Colorado System
    • Foundations of Digital Marketing: University of Maryland, College Park
    • Introduction to Semiconductor Process 2: Korea Advanced Institute of Science and Technology(KAIST)
    • Security for Blockchain and DApps: LearnQuest
    • Art of the MOOC: Experiments with Sound: Duke University
    • DevOps and AI on AWS: Upgrading Apps with Generative AI: Amazon Web Services
    • Elasticsearch 8 and the Elastic Stack: In-Depth and Hands-On: Packt

    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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