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    Results for "advanced statistics"

    • D

      Duke University

      MLOps | Machine Learning Operations

      Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Data Ethics, Application Deployment, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, Software Testing, Data Import/Export, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Docker (Software), Rust (Programming Language)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      450 reviews

      Advanced · Specialization · 3 - 6 Months

    • I

      IBM

      Deep Learning with Keras and Tensorflow

      Skills you'll gain: Keras (Neural Network Library), Reinforcement Learning, Unsupervised Learning, Deep Learning, Tensorflow, Generative AI, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Image Analysis, Time Series Analysis and Forecasting, Natural Language Processing, Performance Tuning

      4.4
      Rating, 4.4 out of 5 stars
      ·
      937 reviews

      Intermediate · Course · 1 - 3 Months

    • R

      Rice University

      Introduction to Mechanics

      Skills you'll gain: Mechanics, Torque (Physics), Physics, Structural Analysis, Mechanical Engineering, Calculus, Engineering Calculations, Engineering Analysis, Physical Science, Mathematical Modeling, Algebra, Applied Mathematics, Geometry, Trigonometry

      4.6
      Rating, 4.6 out of 5 stars
      ·
      254 reviews

      Intermediate · Specialization · 1 - 3 Months

    • C

      Coursera Project Network

      Statistics For Data Science

      Skills you'll gain: Correlation Analysis, Probability & Statistics, Statistics, Statistical Analysis, Data Analysis, Data Science, Probability Distribution, Descriptive Statistics, Statistical Inference

      3.9
      Rating, 3.9 out of 5 stars
      ·
      33 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • 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

    • Status: New
      New
      Status: Free
      Free
      J

      Johns Hopkins University

      Advanced Business Analytics: Excel Optimization & Simulation

      Skills you'll gain: Resource Allocation, Simulation and Simulation Software, Microsoft Excel, Business Analytics, Data-Driven Decision-Making, Operational Analysis, Transportation Operations, Analytics, Business Operations, Risk Analysis, Process Optimization, Statistical Methods, Business Modeling, Logistics

      5
      Rating, 5 out of 5 stars
      ·
      20 reviews

      Mixed · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Apply Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Data Ethics, Computer Vision, Deep Learning, Applied Machine Learning, Machine Learning, Unsupervised Learning, Information Privacy, Artificial Intelligence

      4.8
      Rating, 4.8 out of 5 stars
      ·
      544 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Alberta

      Sample-based Learning Methods

      Skills you'll gain: Reinforcement Learning, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of Leeds

      Exploratory Data Analysis

      Skills you'll gain: Exploratory Data Analysis, Data Cleansing, Statistical Modeling, Statistics, Data Analysis, Statistical Inference, R Programming, Descriptive Statistics, Box Plots, Data Visualization Software, Histogram, Probability, Simulations

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      University of Cape Town

      Doing Clinical Research: Biostatistics with the Wolfram Language

      Skills you'll gain: Descriptive Statistics, Data Literacy, Exploratory Data Analysis, Plot (Graphics), Statistical Analysis, Statistical Visualization, Statistical Programming, Biostatistics, Statistical Hypothesis Testing, Quantitative Research, Probability & Statistics, Deep Learning, Data Manipulation, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      49 reviews

      Beginner · Course · 1 - 4 Weeks

    • K

      Kennesaw State University

      Six Sigma Tools for Improve and Control

      Skills you'll gain: Six Sigma Methodology, Process Improvement, Process Optimization, Correlation Analysis, Statistical Hypothesis Testing, Lean Six Sigma, Kaizen Methodology, Quality Improvement, Regression Analysis, Statistical Process Controls, Continuous Improvement Process, Process Capability, Quality Management, Project Management, Cost Benefit Analysis, Statistical Inference, Document Control

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Beginner · Course · 1 - 3 Months

    • 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
      ·
      373 reviews

      Beginner · Course · 1 - 4 Weeks

    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
    statistical analysis and advanced techniques
    advanced linear models for data science 2: statistical linear models
    1…333435…263

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

    • MLOps | Machine Learning Operations: Duke University
    • Deep Learning with Keras and Tensorflow: IBM
    • Introduction to Mechanics: Rice University
    • Statistics For Data Science: Coursera Project Network
    • Clinical Data Science: University of Colorado System
    • Advanced Business Analytics: Excel Optimization & Simulation: Johns Hopkins University
    • Apply Generative Adversarial Networks (GANs): DeepLearning.AI
    • Sample-based Learning Methods: University of Alberta
    • Exploratory Data Analysis: University of Leeds
    • Doing Clinical Research: Biostatistics with the Wolfram Language: University of Cape Town

    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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