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    Results for "advanced statistics"

    • Status: Free
      Free
      G

      Georgia Institute of Technology

      Materials Data Sciences and Informatics

      Skills you'll gain: Dimensionality Reduction, Data Science, Data Mining, Data Integration, Data-Driven Decision-Making, Information Management, Data Processing, Manufacturing Processes, Engineering Analysis, Process Engineering, Big Data, Chemical Engineering, Predictive Modeling, Innovation, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      344 reviews

      Intermediate · Course · 1 - 3 Months

    • D

      Databricks

      Introduction to Computational Statistics for Data Scientists

      Skills you'll gain: Bayesian Statistics, Databricks, Sampling (Statistics), Statistical Modeling, Probability, Classification And Regression Tree (CART), Jupyter, Regression Analysis, Statistical Programming, Predictive Modeling, Statistical Analysis, Statistical Machine Learning, Probability Distribution, Data Science, Markov Model, Statistics, NumPy, Simulations, Mathematical Software, Statistical Inference

      4
      Rating, 4 out of 5 stars
      ·
      109 reviews

      Beginner · Specialization · 1 - 3 Months

    • U

      University of California, Davis

      Essential Design Principles for Tableau

      Skills you'll gain: Data Visualization Software, Tableau Software, Exploratory Data Analysis, Data Presentation, Data Analysis, Web Content Accessibility Guidelines, User Interface and User Experience (UI/UX) Design, Usability, Design Elements And Principles, Color Theory, Data Ethics, Human Factors, Aesthetics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado System

      Clinical Data Science

      Skills you'll gain: Tidyverse (R Package), Clinical Data Management, Extract, Transform, Load, Data Modeling, Clinical Research, R Programming, Data Manipulation, Predictive Modeling, Database Design, Google Cloud Platform, Intensive Care Unit, Data Ethics, Data Quality, Risk Modeling, Natural Language Processing, Health Informatics, Statistical Modeling, Bioinformatics, Text Mining, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      468 reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Managing Data Analysis

      Skills you'll gain: Exploratory Data Analysis, Data Analysis, Data Presentation, Data Management, Management Training And Development, Technical Communication, Team Management, Analytical Skills, Team Leadership, Statistical Inference, Statistical Modeling, Communication

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      Y

      Yale University

      Rocket Science for Everyone

      Skills you'll gain: Global Positioning Systems, Geospatial Information and Technology, Geographic Information Systems, Physical Science, Spatial Analysis, Mechanics, Engineering, Physics, Electrical Engineering

      4.9
      Rating, 4.9 out of 5 stars
      ·
      527 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Text Mining and Analytics

      Skills you'll gain: Text Mining, Data Mining, Unstructured Data, Statistical Analysis, Natural Language Processing, Analytics, Data Analysis, Unsupervised Learning, Probability & Statistics, Regression Analysis, Predictive Modeling, Supervised Learning, Machine Learning Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      734 reviews

      Mixed · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Advanced Computer Vision with TensorFlow

      Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Applied Machine Learning, Deep Learning, Feature Engineering, Artificial Neural Networks, Visualization (Computer Graphics), Data Processing, Network Architecture

      4.7
      Rating, 4.7 out of 5 stars
      ·
      520 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      GenAI for Executives & Business Leaders: An Introduction

      Skills you'll gain: Generative AI, Data Ethics, Artificial Intelligence, Business Transformation, Business Leadership, Business Ethics, Governance, Digital Transformation, Data-Driven Decision-Making, Business Strategies, Customer experience improvement, Customer Service

      4.7
      Rating, 4.7 out of 5 stars
      ·
      366 reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Launching into Machine Learning

      Skills you'll gain: Data Quality, Exploratory Data Analysis, Machine Learning, MLOps (Machine Learning Operations), Applied Machine Learning, Scikit Learn (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Google Cloud Platform, Machine Learning Algorithms, Data Analysis, Predictive Modeling, Big Data, Classification And Regression Tree (CART), Regression Analysis, Data Processing, Sampling (Statistics), Test Data, Performance Tuning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.3K reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Basic Statistics in Python (Correlations and T-tests)

      Skills you'll gain: Exploratory Data Analysis, Box Plots, Correlation Analysis, Data Visualization, Scatter Plots, Data Cleansing, Data Manipulation, Pandas (Python Package), Statistical Hypothesis Testing, Descriptive Statistics, Statistical Analysis, Data Analysis, Probability & Statistics, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      34 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • I

      IBM

      Supervised Machine Learning: Regression

      Skills you'll gain: Supervised Learning, Applied Machine Learning, Regression Analysis, Machine Learning, Statistical Machine Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      731 reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
    advanced linear models for data science 2: statistical linear models
    1…343536…262

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

    • Materials Data Sciences and Informatics: Georgia Institute of Technology
    • Introduction to Computational Statistics for Data Scientists: Databricks
    • Essential Design Principles for Tableau: University of California, Davis
    • Clinical Data Science: University of Colorado System
    • Managing Data Analysis: Johns Hopkins University
    • Rocket Science for Everyone: Yale University
    • Text Mining and Analytics: University of Illinois Urbana-Champaign
    • Advanced Computer Vision with TensorFlow: DeepLearning.AI
    • GenAI for Executives & Business Leaders: An Introduction: IBM
    • Launching into Machine Learning: Google Cloud

    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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