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    Results for "advanced statistics"

    • D

      DeepLearning.AI

      Generative AI for Everyone

      Skills you'll gain: Prompt Engineering, Generative AI, Large Language Modeling, OpenAI, ChatGPT, Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Business Process Automation, Automation, Ethical Standards And Conduct, Cloud Applications

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • 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
      ·
      64 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: Free
      Free
      J

      Johns Hopkins University

      Business Analytics with Excel: Elementary to Advanced

      Skills you'll gain: Risk Modeling, Operations Research, Regression Analysis, Microsoft Excel, Business Analytics, Risk Analysis, Business Process Modeling, Business Modeling, Data Modeling, Resource Allocation, Statistical Analysis, Process Optimization, Financial Analysis, Predictive Analytics, Transportation Operations, Complex Problem Solving, Linear Algebra

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      I

      IBM

      IBM Java Developer

      Skills you'll gain: Spring Framework, Cloud-Native Computing, Software Development Life Cycle, Hibernate (Java), Docker (Software), Git (Version Control System), GitHub, HTML and CSS, Object Oriented Programming (OOP), Spring Boot, Object-Relational Mapping, Development Environment, Web Design and Development, Object Oriented Design, Large Language Modeling, Java Programming, Generative AI, Interviewing Skills, Java, Professional Networking

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • R

      Rice University

      Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions

      Skills you'll gain: Descriptive Statistics, Probability & Statistics, Probability Distribution, Business Analytics, Microsoft Excel, Data Analysis, Statistical Analysis, Box Plots, Sampling (Statistics), Correlation Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.6K reviews

      Mixed · 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, Predictive Modeling, Statistical Hypothesis Testing, 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

    • M

      Meta

      Advanced React

      Skills you'll gain: Jest (JavaScript Testing Framework), React.js, Web Development Tools, JavaScript Frameworks, API Design, Unit Testing, UI Components, Javascript, JSON, Integration Testing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.4K reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      BI Foundations with SQL, ETL and Data Warehousing

      Skills you'll gain: Data Warehousing, Extract, Transform, Load, Apache Airflow, Linux Commands, SQL, IBM Cognos Analytics, Data Pipelines, Apache Kafka, Bash (Scripting Language), Shell Script, Dashboard, File Management, Star Schema, Unix Shell, IBM DB2, Business Intelligence, Interactive Data Visualization, Relational Databases, Stored Procedure, Databases

      4.6
      Rating, 4.6 out of 5 stars
      ·
      24K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      Imperial College London

      Introduction to Statistics & Data Analysis in Public Health

      Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, Statistical Software, R Programming, Statistics, Public Health, Descriptive Statistics, Probability Distribution, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Advanced Learning Algorithms

      Skills you'll gain: Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Artificial Intelligence, Supervised Learning, Deep Learning, Random Forest Algorithm, Artificial Neural Networks, Performance Tuning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      7.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Microsoft

      Work Smarter with Microsoft Excel

      Skills you'll gain: Microsoft Excel, Excel Formulas, Data Visualization, Spreadsheet Software, Microsoft 365, Productivity Software, Data Import/Export, Data Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.8K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      IBM Data Analytics with Excel and R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Relational Databases, Big Data, Data Visualization Software, Ggplot2, Database Design, Data Analysis, IBM Cognos Analytics, Statistical Analysis, Data Presentation, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…678…262

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

    • Generative AI for Everyone: DeepLearning.AI
    • Advanced Microsoft Power BI: Edureka
    • Business Analytics with Excel: Elementary to Advanced: Johns Hopkins University
    • IBM Java Developer: IBM
    • Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions: Rice University
    • Data Science: Johns Hopkins University
    • Advanced React: Meta
    • BI Foundations with SQL, ETL and Data Warehousing: IBM
    • Introduction to Statistics & Data Analysis in Public Health: Imperial College London
    • Advanced Learning Algorithms: DeepLearning.AI

    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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