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    Results for "advanced statistics"

    • P

      Packt

      Foundations of Data Analysis with Pandas and Python

      Skills you'll gain: Data Import/Export, Pandas (Python Package), Pivot Tables And Charts, Jupyter, Microsoft Excel, Data Analysis, Data Manipulation, Python Programming, Data Structures, Integrated Development Environments, Development Environment, Software Installation, Object Oriented Programming (OOP)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      16 reviews

      Beginner · Course · 1 - 4 Weeks

    • L

      LearnQuest

      Introduction to Data Science and scikit-learn in Python

      Skills you'll gain: Feature Engineering, Exploratory Data Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data Manipulation, NumPy, Data Analysis, Data Processing, Python Programming, Regression Analysis, Predictive Modeling, Machine Learning, Classification And Regression Tree (CART), Statistical Methods, Computer Programming, Data Structures

      3.7
      Rating, 3.7 out of 5 stars
      ·
      49 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IIMA - IIM Ahmedabad

      How to Transform Digitally?

      Skills you'll gain: Digital Transformation, Business Transformation, Stakeholder Engagement, Organizational Change, Change Management, Business Modeling, Technology Strategies, Enterprise Architecture, Cloud Computing Architecture, Governance, Business Technologies, Operational Excellence, Workforce Development, Cybersecurity

      4.8
      Rating, 4.8 out of 5 stars
      ·
      28 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Introduction to R Programming and Tidyverse

      Skills you'll gain: Rmarkdown, Ggplot2, Tidyverse (R Package), R Programming, Data Visualization Software, Statistical Programming, Data Manipulation, Statistical Reporting, Data Analysis, Data Wrangling, Software Installation, Debugging

      4.2
      Rating, 4.2 out of 5 stars
      ·
      47 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Getting Started with Facebook Pixel

      Skills you'll gain: Target Audience, Social Media Marketing, Social Media Campaigns, Online Advertising, Social Media, Web Analytics

      4.2
      Rating, 4.2 out of 5 stars
      ·
      22 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • B

      Board Infinity

      Essential Testing Techniques in Software Development

      Skills you'll gain: Test Case, Software Testing, Integration Testing, Software Development Life Cycle, System Testing, Acceptance Testing, Maintainability, Regression Testing, Test Planning, Software Quality Assurance, Unit Testing, Functional Testing, User Acceptance Testing (UAT)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7 reviews

      Beginner · Course · 1 - 4 Weeks

    • R

      Rice University

      Introduction to Archaeology: Knowing The Past

      Skills you'll gain: Ancient History, Anthropology, Scientific Methods, Peer Review, Investigation, Social Sciences, Research, World History, Culture, Research Methodologies, Cultural Diversity

      4.9
      Rating, 4.9 out of 5 stars
      ·
      16 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      University of London

      Doing Economics: Measuring Climate Change

      Skills you'll gain: Microsoft Excel, Environmental Policy, Data Analysis, Data Visualization, Descriptive Statistics, Correlation Analysis, Policy Analysis, Environmental Issue, Scatter Plots, Environmental Science, Economics, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      52 reviews

      Beginner · Course · 1 - 4 Weeks

    • L

      L&T EduTech

      Strategies for Heavy Lifting

      Skills you'll gain: Structural Engineering, Construction Engineering, Construction, Engineering Management, Equipment Design, Construction Management, Engineering Practices, Engineering Plans And Specifications, Hydraulics, Architecture and Construction, Mechanics, Engineering, Engineering Design Process, Civil Engineering, Structural Analysis, Safety Assurance, Engineering Calculations, Mechanical Engineering, Engineering Analysis, Estimation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      8 reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: New
      New
      P

      Packt

      CompTIA Security+ Certification (SY0-701): The Total Course

      Skills you'll gain: Penetration Testing, Incident Response, Network Security, Intrusion Detection and Prevention, Cybersecurity, Computer Security Incident Management, Application Security, Open Web Application Security Project (OWASP), Information Systems Security, Identity and Access Management, Vulnerability Assessments, Security Strategy, Cryptography, Security Testing, Secure Coding, Encryption, Risk Management Framework, Command-Line Interface, Virtual Private Networks (VPN), Threat Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      8 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      M

      Microsoft

      Microsoft Azure for AI and Machine Learning

      Skills you'll gain: MLOps (Machine Learning Operations), Microsoft Azure, Artificial Intelligence and Machine Learning (AI/ML), Application Deployment, Data Pipelines, Network Troubleshooting, Cloud Computing, Software Versioning, CI/CD, Continuous Monitoring, Data Storage, Scalability, Data Quality, Data Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 3 Months

    • N

      Novartis

      Lead Selection & Optimization

      Skills you'll gain: Pharmacology, Pharmaceuticals, Clinical Research, Biochemistry, Chemistry, Laboratory Research, Infectious Diseases, Research Design

      5
      Rating, 5 out of 5 stars
      ·
      21 reviews

      Intermediate · Course · 1 - 4 Weeks

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
    advanced statistical techniques for data science
    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
    statistical analysis and advanced techniques
    advanced linear models for data science 2: statistical linear models
    1…115116117…265

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

    • Foundations of Data Analysis with Pandas and Python: Packt
    • Introduction to Data Science and scikit-learn in Python: LearnQuest
    • How to Transform Digitally?: IIMA - IIM Ahmedabad
    • Introduction to R Programming and Tidyverse: University of Colorado Boulder
    • Getting Started with Facebook Pixel: Coursera Project Network
    • Essential Testing Techniques in Software Development: Board Infinity
    • Introduction to Archaeology: Knowing The Past: Rice University
    • Doing Economics: Measuring Climate Change: University of London
    • Strategies for Heavy Lifting: L&T EduTech
    • CompTIA Security+ Certification (SY0-701): The Total Course: 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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