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    Results for "advanced statistics"

    • P

      Packt

      Advanced Frontend Development and Deployment

      Skills you'll gain: React Redux, Application Deployment, React.js, Full-Stack Web Development, Node.JS, Continuous Deployment, Authentications, User Accounts, Development Environment, Front-End Web Development, User Interface (UI), Application Security, Data Validation

      Advanced · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      IoT Communications

      Skills you'll gain: Internet Of Things, Telecommunications, Distributed Computing, Wireless Networks, General Networking, Network Routing, Embedded Software, Network Protocols, Algorithms, Geographic Information Systems

      4.7
      Rating, 4.7 out of 5 stars
      ·
      63 reviews

      Intermediate · Course · 1 - 4 Weeks

    • P

      Packt

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

      Skills you'll gain: Data Presentation, Kibana, Data Import/Export, Restful API, Data Mapping, Data Visualization Software, Dashboard, Data Integration, Query Languages, Time Series Analysis and Forecasting, Apache Kafka, Data Modeling, Histogram, Cloud Management, Amazon Web Services, Software Installation, Application Deployment, Text Mining, Scalability, System Monitoring

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11 reviews

      Beginner · Specialization · 1 - 3 Months

    • P

      Packt

      Project Finance & Excel: Build Financial Models from Scratch

      Skills you'll gain: Financial Modeling, Project Finance, Timelines, Return On Investment, Financial Statements, Financial Analysis, Balance Sheet, Construction Management, Capital Expenditure, Operating Cost, Income Statement, Cash Flow Forecasting, Microsoft Excel, Scheduling, Cash Flows, Revenue Forecasting

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      Learn Spring Boot in 100 Steps - Beginner to Expert

      Skills you'll gain: JUnit, Apache Maven, Spring Framework, Spring Boot, Build Tools, Restful API, Unit Testing, Hibernate (Java), Integration Testing, Gradle, Java, Object-Relational Mapping, Software Testing, Bootstrap (Front-End Framework), Database Management, UI Components, Web Applications, Application Programming Interface (API), Application Frameworks, Test Case

      4.3
      Rating, 4.3 out of 5 stars
      ·
      6 reviews

      Intermediate · Specialization · 1 - 3 Months

    • J

      Johns Hopkins University

      Advanced Project Management and Leadership

      Skills you'll gain: Project Closure, Project Portfolio Management, Negotiation, Agile Methodology, Product Roadmaps, Project Management, Project Performance, Product Lifecycle Management, Project Risk Management, Innovation, Auditing, Resource Allocation, New Product Development, Team Leadership, Leadership

      4.8
      Rating, 4.8 out of 5 stars
      ·
      13 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      Lean Six Sigma - Yellow Belt

      Skills you'll gain: Lean Six Sigma, Process Improvement, Continuous Improvement Process, Lean Methodologies, Process Analysis, Quality Management, Waste Minimization, Analysis, Benchmarking, Project Management, Stakeholder Management, Root Cause Analysis

      5
      Rating, 5 out of 5 stars
      ·
      7 reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Advanced Malware and Network Anomaly Detection

      Skills you'll gain: Anomaly Detection, Intrusion Detection and Prevention, Malware Protection, Continuous Monitoring, Threat Detection, Network Analysis, Cybersecurity, System Design and Implementation, Network Security, Machine Learning Software, Machine Learning Methods, Performance Testing, Machine Learning Algorithms, Machine Learning, Supervised Learning, Microsoft Windows

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      Microsoft

      Cloud Computing Essentials with Azure Management

      Skills you'll gain: Cloud Management, Microsoft Azure, Cloud Computing Architecture, Cloud Computing, Infrastructure As A Service (IaaS), Cloud Infrastructure, Software As A Service, Infrastructure as Code (IaC), Cloud Security, System Monitoring, Scalability

      4.5
      Rating, 4.5 out of 5 stars
      ·
      13 reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Using Sensors With Your Raspberry Pi

      Skills you'll gain: Data Processing, Technical Design, Data Science, Embedded Software, Data Cleansing, Data Analysis Software, Statistical Methods, Analytical Skills, Real Time Data, Data Quality

      4.8
      Rating, 4.8 out of 5 stars
      ·
      8 reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      Illinois Tech

      Bayesian Computational Statistics

      Skills you'll gain: Bayesian Statistics, Data Analysis, Statistical Inference, Regression Analysis, Statistical Methods, Statistical Analysis, Statistical Modeling, Statistical Programming, Statistical Software, R Programming, Markov Model, Probability, Simulations, Probability Distribution

      Build toward a degree

      Intermediate · Course · 1 - 3 Months

    • I

      Indian Institute of Science

      Micro Electromechanical Systems

      Skills you'll gain: Electronics Engineering, Semiconductors, Electronics, Hardware Design, Electronic Systems, Embedded Systems, Mechanical Engineering, Chemical and Biomedical Engineering, Manufacturing Processes, Laboratory Equipment, Process Engineering, Laboratory Testing, 3D Modeling

      4.9
      Rating, 4.9 out of 5 stars
      ·
      17 reviews

      Beginner · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
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    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
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    advanced linear models for data science 2: statistical linear models
    1…117118119…265

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

    • Advanced Frontend Development and Deployment: Packt
    • IoT Communications: University of Illinois Urbana-Champaign
    • Elasticsearch 8 and the Elastic Stack: In-Depth and Hands-On: Packt
    • Project Finance & Excel: Build Financial Models from Scratch: Packt
    • Learn Spring Boot in 100 Steps - Beginner to Expert: Packt
    • Advanced Project Management and Leadership: Johns Hopkins University
    • Lean Six Sigma - Yellow Belt: Packt
    • Advanced Malware and Network Anomaly Detection: Johns Hopkins University
    • Cloud Computing Essentials with Azure Management: Microsoft
    • Using Sensors With Your Raspberry Pi: Johns Hopkins University

    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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