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    Results for "advanced statistics"

    • K

      Korea Advanced Institute of Science and Technology(KAIST)

      Biochemical Principles of Energy Metabolism

      Skills you'll gain: Biochemistry, Respiration, Pathology, Biology, Life Sciences, Nutrition and Diet, Chronic Diseases, Molecular Biology, Clinical Nutrition, Internal Medicine, Oncology

      4.8
      Rating, 4.8 out of 5 stars
      ·
      814 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Caltech

      The Science of the Solar System

      Skills you'll gain: Science and Research, Research, Physical Science, Scientific Methods, Life Sciences, Physics, Water Resources, Advanced Mathematics, Chemistry, Environment, Biology

      4.8
      Rating, 4.8 out of 5 stars
      ·
      799 reviews

      Mixed · Course · 1 - 3 Months

    • N

      Northwestern University

      Modern Robotics, Course 1: Foundations of Robot Motion

      Skills you'll gain: Engineering, Mechanics, Mathematical Modeling, Torque (Physics), Simulation and Simulation Software, Matlab, Linear Algebra, Angular

      4.7
      Rating, 4.7 out of 5 stars
      ·
      987 reviews

      Intermediate · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Custom Models, Layers, and Loss Functions with TensorFlow

      Skills you'll gain: Tensorflow, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Network Model, Network Architecture, API Design, Object Oriented Programming (OOP)

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.1K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Michigan

      Advanced Styling with Responsive Design

      Skills you'll gain: Responsive Web Design, HTML and CSS, Web Design, Cascading Style Sheets (CSS), Bootstrap (Front-End Framework), Wireframing, Front-End Web Development, Browser Compatibility, Usability, User Interface (UI), Web Content Accessibility Guidelines, Mobile Development Tools

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Exploratory Data Analysis

      Skills you'll gain: Exploratory Data Analysis, Data Visualization, Plot (Graphics), Ggplot2, Dimensionality Reduction, Data Visualization Software, R Programming, Scatter Plots, Graphing, Box Plots, Data Analysis, Histogram, Statistical Analysis, Unsupervised Learning, Color Theory

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      N

      Northwestern University

      Fundamentals of Digital Image and Video Processing

      Skills you'll gain: Image Analysis, Digital Communications, Computer Vision, Data Processing, Visualization (Computer Graphics), Medical Imaging, Electrical and Computer Engineering, Motion Graphics, Linear Algebra, Color Theory, Bayesian Statistics, Applied Mathematics, Sampling (Statistics), Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 3 Months

    • I

      Imperial College London

      Epidemiology for Public Health

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

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

      Beginner · Specialization · 1 - 3 Months

    • U

      University of Pennsylvania

      A Crash Course in Causality: Inferring Causal Effects from Observational Data

      Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Statistical Software, Statistical Modeling, Statistical Inference, Data Analysis, Probability & Statistics, Regression Analysis, Research Design, Graph Theory

      4.7
      Rating, 4.7 out of 5 stars
      ·
      564 reviews

      Intermediate · Course · 1 - 3 Months

    • É

      École Polytechnique Fédérale de Lausanne

      Digital Signal Processing

      Skills you'll gain: Digital Communications, Image Analysis, Telecommunications, Electrical Engineering, Electrical and Computer Engineering, Embedded Systems, Electronic Systems, Electronics Engineering, Computer Engineering, Engineering Calculations, Electronics, Programming Principles, Engineering Analysis, Numerical Analysis, Advanced Mathematics, Algorithms, Linear Algebra, Mathematical Modeling, Calculus, Applied Mathematics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      778 reviews

      Intermediate · Specialization · 3 - 6 Months

    • M

      Microsoft

      Microsoft Azure Data Scientist Associate (DP-100) Exam Prep

      Skills you'll gain: Databricks, Unsupervised Learning, PySpark, Microsoft Azure, Apache Spark, Scikit Learn (Machine Learning Library), MLOps (Machine Learning Operations), PyTorch (Machine Learning Library), Exploratory Data Analysis, Deep Learning, Data Visualization, Regression Analysis, Data Science, Predictive Modeling, Data Analysis, Applied Machine Learning, Image Analysis, Pandas (Python Package), Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing

      4.2
      Rating, 4.2 out of 5 stars
      ·
      545 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • C

      Coursera Project Network

      COVID19 Data Analysis Using Python

      Skills you'll gain: Correlation Analysis, Seaborn, Data Cleansing, Data Visualization, Statistical Analysis, Data Manipulation, Data Analysis, Exploratory Data Analysis, Pandas (Python Package), Data Integration, Infectious Diseases

      4.5
      Rating, 4.5 out of 5 stars
      ·
      2K reviews

      Intermediate · Guided Project · Less Than 2 Hours

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…293031…263

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

    • Biochemical Principles of Energy Metabolism: Korea Advanced Institute of Science and Technology(KAIST)
    • The Science of the Solar System: Caltech
    • Modern Robotics, Course 1: Foundations of Robot Motion: Northwestern University
    • Custom Models, Layers, and Loss Functions with TensorFlow: DeepLearning.AI
    • Advanced Styling with Responsive Design: University of Michigan
    • Exploratory Data Analysis: Johns Hopkins University
    • Fundamentals of Digital Image and Video Processing: Northwestern University
    • Epidemiology for Public Health: Imperial College London
    • A Crash Course in Causality: Inferring Causal Effects from Observational Data: University of Pennsylvania
    • Digital Signal Processing: École Polytechnique Fédérale de Lausanne

    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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