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    Results for "advanced statistics"

    • I

      IBM

      Deep Learning and Reinforcement Learning

      Skills you'll gain: Generative AI, Reinforcement Learning, Deep Learning, Unsupervised Learning, Artificial Neural Networks, PyTorch (Machine Learning Library), Keras (Neural Network Library), Machine Learning Algorithms, Tensorflow, Computer Vision, Dimensionality Reduction, Natural Language Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      253 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      Imperial College London

      Measuring Disease in Epidemiology

      Skills you'll gain: Epidemiology, Public Health, Preventative Care, Biostatistics, Program Evaluation, General Medical Tests and Procedures, Probability & Statistics, Risk Analysis, Quantitative Research, Health Policy, Science and Research, Statistical Methods, Research

      4.7
      Rating, 4.7 out of 5 stars
      ·
      769 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of North Texas

      Research Design: Inquiry and Discovery

      Skills you'll gain: Research Design, Research, Research Methodologies, Surveys, Qualitative Research, Scientific Methods, Business Research, Data Collection, Analysis, Ethical Standards And Conduct, Decision Making, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      406 reviews

      Beginner · Course · 1 - 4 Weeks

    • N

      Northwestern University

      Modern Robotics, Course 2: Robot Kinematics

      Skills you'll gain: Mathematical Modeling, Machine Controls, Automation Engineering, Engineering Calculations, Applied Mathematics, Engineering Analysis, Mechanics, Computational Logic, Simulation and Simulation Software, Virtual Environment, Torque (Physics), Numerical Analysis, Linear Algebra, Trigonometry, Control Systems

      4.9
      Rating, 4.9 out of 5 stars
      ·
      295 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      Imperial College London

      Global Disease Masterclass

      Skills you'll gain: Infectious Diseases, Epidemiology, Public Health and Disease Prevention, Public Health, Health Disparities, Cardiology, Chronic Diseases, Microbiology, Community Health, Health Systems, Health Policy, Socioeconomics, Preventative Care, Health Care, Health Assessment, Biostatistics, Data Analysis, Policy Analysis, Trend Analysis, Medical Science and Research

      4.8
      Rating, 4.8 out of 5 stars
      ·
      315 reviews

      Beginner · Specialization · 1 - 3 Months

    • L

      LearnQuest

      Machine Learning for Supply Chains

      Skills you'll gain: Image Analysis, Exploratory Data Analysis, Time Series Analysis and Forecasting, Data Wrangling, Operations Research, NumPy, Demand Planning, Data Manipulation, Feature Engineering, Supervised Learning, Inventory Management System, Supply Chain, Applied Machine Learning, Inventory Management, Trend Analysis, Data Visualization, Data Transformation, Customer Demand Planning, Predictive Modeling, Anomaly Detection

      3.6
      Rating, 3.6 out of 5 stars
      ·
      76 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Text Retrieval and Search Engines

      Skills you'll gain: Text Mining, Natural Language Processing, Data Mining, Unstructured Data, Big Data, Web Analytics and SEO, Machine Learning, Information Architecture, Statistical Methods, Algorithms, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      959 reviews

      Mixed · Course · 1 - 3 Months

    • S

      Stanford University

      Probabilistic Graphical Models 3: Learning

      Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Markov Model, Machine Learning, Statistical Modeling, Network Analysis, Probability Distribution, Statistical Methods, Probability & Statistics, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      303 reviews

      Advanced · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Precalculus through Data and Modelling

      Skills you'll gain: Data Analysis, Applied Mathematics, Mathematical Modeling, Graphing, Trigonometry, Analytical Skills, R Programming, General Mathematics, Statistics, Algebra, Systems Of Measurement, Correlation Analysis, Regression Analysis, Calculus, Geometry

      4.7
      Rating, 4.7 out of 5 stars
      ·
      303 reviews

      Beginner · Specialization · 3 - 6 Months

    • P

      Packt

      Advanced Data Analysis and Visualization with Pandas

      Skills you'll gain: Matplotlib, Pandas (Python Package), Data Import/Export, Data Visualization Software, Microsoft Excel, NumPy, Time Series Analysis and Forecasting, Data Analysis, Data Manipulation, Python Programming

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6 reviews

      Advanced · Course · 1 - 3 Months

    • I

      IE Business School

      Globalización, Crecimiento Económico y Estabilidad

      Skills you'll gain: Financial Policy, Economics, Policy, and Social Studies, Economics, Public Policies, International Finance, Policy Analysis, International Relations, Economic Development, Tax, Socioeconomics, Trend Analysis, Global Marketing, Business Economics, Political Sciences, Analysis, Fiscal Management, Supply And Demand, Business Risk Management, World History, Policty Analysis, Research, and Development

      4.8
      Rating, 4.8 out of 5 stars
      ·
      694 reviews

      Beginner · Specialization · 3 - 6 Months

    • S

      SAS

      Doing More with SAS Programming

      Skills you'll gain: SAS (Software), Data Manipulation, Consolidation, Data Transformation, Data Processing, Data Analysis, Data Presentation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      939 reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…474849…263

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

    • Deep Learning and Reinforcement Learning: IBM
    • Measuring Disease in Epidemiology: Imperial College London
    • Research Design: Inquiry and Discovery: University of North Texas
    • Modern Robotics, Course 2: Robot Kinematics: Northwestern University
    • Global Disease Masterclass: Imperial College London
    • Machine Learning for Supply Chains: LearnQuest
    • Text Retrieval and Search Engines: University of Illinois Urbana-Champaign
    • Probabilistic Graphical Models 3: Learning: Stanford University
    • Precalculus through Data and Modelling: Johns Hopkins University
    • Advanced Data Analysis and Visualization with Pandas: 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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