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    Results for "advanced statistics"

    • G

      Google

      Google IT Automation with Python

      Skills you'll gain: Git (Version Control System), GitHub, Version Control, Cloud Services, Debugging, Puppet (Configuration Management Tool), Infrastructure as Code (IaC), Bash (Scripting Language), Configuration Management, CI/CD, Cloud Computing, Technical Communication, Docker (Software), Unit Testing, Scripting, Network Troubleshooting, Web Services, Python Programming, Restful API, Programming Principles

      4.7
      Rating, 4.7 out of 5 stars
      ·
      48K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      I

      IBM

      IBM Java Developer

      Skills you'll gain: Docker (Software), Containerization, Spring Framework, Cloud-Native Computing, Software Development Life Cycle, Restful API, Database Design, Hibernate (Java), Continuous Integration, Git (Version Control System), GitHub, Model View Controller, Microservices, HTML and CSS, Object Oriented Programming (OOP), Spring Boot, Object-Relational Mapping, Large Language Modeling, Java Programming, Interviewing Skills

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • V

      Vanderbilt University

      Generative AI Automation

      Skills you'll gain: Prompt Engineering, ChatGPT, Ideation, Verification And Validation, Data Validation, Data Presentation, Productivity, Generative AI, Document Management, Data Synthesis, Image Analysis, Data Capture, Artificial Intelligence, OpenAI, Large Language Modeling, Data Analysis, Organizational Skills, Risk Management Framework, Computer Vision, Microsoft Excel

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • D
      S

      Multiple educators

      Machine Learning

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), Artificial Intelligence, NumPy, Predictive Modeling, Deep Learning, Reinforcement Learning, Random Forest Algorithm, Feature Engineering

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      33K reviews

      Beginner · Specialization · 1 - 3 Months

    • E

      Edureka

      Advanced Microsoft Power BI

      Skills you'll gain: Dashboard, Power BI, Data Transformation, Data Modeling, Interactive Data Visualization, Microsoft Power Platform, Data Visualization Software, Business Intelligence, Predictive Analytics, Microsoft Excel, Data Analysis, Data Integration, Data Cleansing, Key Performance Indicators (KPIs)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      66 reviews

      Advanced · Course · 1 - 4 Weeks

    • P

      PwC

      Data Visualization with Advanced Excel

      Skills you'll gain: Data Presentation, Dashboard, Data Storytelling, Data Visualization Software, Microsoft Excel, Spreadsheet Software, Excel Formulas, Graphing, Pivot Tables And Charts, Data Modeling, Databases, Data Analysis, Simulation and Simulation Software

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3K reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Data Science

      Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Statistical Hypothesis Testing, Predictive Modeling, Data Wrangling, Data Visualization, Plotly, Machine Learning Algorithms, Plot (Graphics), Knitr

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Data Engineering Foundations

      Skills you'll gain: SQL, Web Scraping, Database Design, MySQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Jupyter, Data Pipelines, Big Data, Database Management, Data Warehousing, Databases, Stored Procedure, Data Manipulation, Automation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      University of London

      Probability and Statistics: To p or not to p?

      Skills you'll gain: Descriptive Statistics, Statistics, Probability & Statistics, Statistical Hypothesis Testing, Data Visualization, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Probability Distribution, Sampling (Statistics), Risk Modeling, Statistical Inference, Mathematical Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.5K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Santa Cruz

      Bayesian Statistics: From Concept to Data Analysis

      Skills you'll gain: Bayesian Statistics, Statistical Inference, Data Analysis, Probability, Statistical Modeling, Statistical Analysis, Microsoft Excel, Probability Distribution, R Programming, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Algebra: Elementary to Advanced

      Skills you'll gain: Algebra, Mathematical Modeling, Graphing, Arithmetic, Advanced Mathematics, Applied Mathematics, General Mathematics, Mathematical Theory & Analysis, Analytical Skills, Probability & Statistics, Geometry

      4.8
      Rating, 4.8 out of 5 stars
      ·
      725 reviews

      Beginner · Specialization · 3 - 6 Months

    • R

      Rutgers the State University of New Jersey

      Supply Chain Management

      Skills you'll gain: Strategic Sourcing, Lean Six Sigma, Lean Manufacturing, Demand Planning, Procurement, Supplier Relationship Management, Forecasting, Process Improvement, Supplier Management, Operations Management, Customer Demand Planning, Purchasing, Production Process, Supply Management, Operational Efficiency, Warehouse Management, Supply Chain Planning, Inventory and Warehousing, Inventory Management System, Transportation, Supply Chain, and Logistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…456…264

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

    • Google IT Automation with Python: Google
    • IBM Java Developer: IBM
    • Generative AI Automation: Vanderbilt University
    • Machine Learning: DeepLearning.AI
    • Advanced Microsoft Power BI: Edureka
    • Data Visualization with Advanced Excel: PwC
    • Data Science: Johns Hopkins University
    • Data Engineering Foundations: IBM
    • Probability and Statistics: To p or not to p?: University of London
    • Bayesian Statistics: From Concept to Data Analysis: University of California, Santa Cruz

    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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