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    • Statistics For Data Science

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    1356 results for "statistics for data science"

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      University of Michigan

      Understanding and Visualizing Data with Python

      Skills you'll gain: Data Science, General Statistics, Probability & Statistics, Python Programming, Statistical Programming, Data Analysis, Data Visualization, Statistical Analysis, Statistical Visualization, Basic Descriptive Statistics, Computer Programming, Plot (Graphics), Programming Principles

      4.7

      (2.5k reviews)

      Beginner · Course · 1-4 Weeks

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      Microsoft

      Microsoft Azure Data Scientist Associate (DP-100)

      Skills you'll gain: Machine Learning, Cloud Computing, Microsoft Azure, Probability & Statistics, Machine Learning Algorithms, Theoretical Computer Science, Algorithms, Apache, Big Data, Data Management, General Statistics, Computer Programming, Regression, Statistical Programming, Python Programming, Applied Machine Learning, Artificial Neural Networks, Computer Vision, Deep Learning, Bayesian Statistics, Business Analysis, Data Analysis, Exploratory Data Analysis, Extract, Transform, Load, Statistical Machine Learning, Experiment, Strategy and Operations

      4.5

      (185 reviews)

      Intermediate · Professional Certificate · 3-6 Months

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      University of Colorado Boulder

      Data Science Foundations: Data Structures and Algorithms

      Skills you'll gain: Theoretical Computer Science, Algorithms, Data Structures, Data Management, Mathematics, Operations Research, Research and Design, Strategy and Operations, Computer Programming, Graph Theory, Programming Principles, Mathematical Theory & Analysis, Computational Logic, Operating Systems, Other Programming Languages, System Programming, Python Programming, Statistical Programming

      4.6

      (286 reviews)

      Advanced · Specialization · 1-3 Months

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      Imperial College London

      TensorFlow 2 for Deep Learning

      Skills you'll gain: Machine Learning, Tensorflow, Deep Learning, Computer Programming, Python Programming, Statistical Programming, Applied Machine Learning, Artificial Neural Networks, Computer Vision, Probability & Statistics, Probability Distribution, Machine Learning Algorithms, Data Visualization, Bayesian Statistics, Natural Language Processing, Advertising, Communication, Marketing, Operations Research, Research and Design

      4.8

      (639 reviews)

      Intermediate · Specialization · 3-6 Months

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      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      Skills you'll gain: Probability & Statistics, General Statistics, Regression, Business Analysis, Data Analysis, Statistical Analysis, Mathematics, Experiment, Statistical Tests, Econometrics, Machine Learning, Machine Learning Algorithms, Calculus, Communication, Linear Algebra, Marketing, R Programming, SQL

      4.1

      (31 reviews)

      Intermediate · Specialization · 3-6 Months

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      IBM Skills Network

      IBM Data Science

      Skills you'll gain: Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Computer Programming, Statistical Visualization, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Extract, Transform, Load, Plot (Graphics), Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Database Application, Geovisualization, Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Database Administration, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing

      4.6

      (108.2k reviews)

      Beginner · Professional Certificate · 3-6 Months

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      Johns Hopkins University

      Advanced Linear Models for Data Science 1: Least Squares

      Skills you'll gain: Probability & Statistics, Mathematics, General Statistics, Linear Algebra, Regression, Econometrics, Experiment, Machine Learning, Algebra, Artificial Neural Networks, Dimensionality Reduction, Machine Learning Algorithms, Probability Distribution, Statistical Machine Learning, Communication

      4.4

      (175 reviews)

      Advanced · Course · 1-3 Months

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      Free

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      The Hong Kong University of Science and Technology

      Python and Statistics for Financial Analysis

      Skills you'll gain: Business Analysis, Computer Programming, Data Analysis, Financial Analysis, Python Programming, Statistical Programming, Finance, Investment Management, Probability & Statistics, Probability Distribution, Statistical Analysis, Basic Descriptive Statistics, Correlation And Dependence, General Statistics, Regression, Risk Management, Securities Trading, Statistical Tests, Accounting, Estimation

      4.4

      (3.7k reviews)

      Intermediate · Course · 1-4 Weeks

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      IBM Skills Network

      Python for Data Science, AI & Development

      Skills you'll gain: Data Analysis, Python Programming, Data Structures, Programming Principles, Algebra, Basic Descriptive Statistics, Exploratory Data Analysis, Computational Logic, Computer Programming, Mathematical Theory & Analysis, Mathematics, Statistical Programming, Theoretical Computer Science

      4.6

      (31k reviews)

      Beginner · Course · 1-3 Months

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      DeepLearning.AI

      AI for Medicine

      Skills you'll gain: Machine Learning, Machine Learning Algorithms, Python Programming, Deep Learning, Machine Learning Software, Statistical Programming, General Statistics, Artificial Neural Networks, Computer Vision, Data Analysis, Probability & Statistics, Algorithms, Applied Machine Learning, Basic Descriptive Statistics, Estimation, Exploratory Data Analysis, Natural Language Processing, Plot (Graphics), Scientific Visualization, Statistical Tests, Statistical Visualization, Theoretical Computer Science, Computer Graphic Techniques, Computer Graphics, Computer Programming, Business Analysis, Data Management, Data Structures, Feature Engineering, Statistical Analysis

      4.7

      (2.2k reviews)

      Intermediate · Specialization · 1-3 Months

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      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Basic Descriptive Statistics, Python Programming, Data Analysis, Data Structures, Data Mining, Exploratory Data Analysis, Statistical Analysis, Correlation And Dependence, Statistical Tests, Data Architecture, Estimation, General Statistics, Linear Algebra, Regression, Statistical Visualization, Computational Logic, Computer Programming, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Programming Principles, Statistical Programming, Theoretical Computer Science

      4.5

      (26.6k reviews)

      Intermediate · Course · 1-4 Weeks

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      CFA Institute

      Data Science for Investment Professionals

      Skills you'll gain: General Statistics, Probability & Statistics, Machine Learning, Data Analysis, Business Analysis, Statistical Analysis, Machine Learning Algorithms, Computer Programming, Python Programming, Statistical Programming, Algorithms, Theoretical Computer Science, Statistical Tests, Regression, Finance, Probability Distribution, Correlation And Dependence, Deep Learning, Econometrics, Forecasting, R Programming, Basic Descriptive Statistics, Data Visualization, Investment Management, Risk Management, Accounting, Communication, Corporate Accouting, Data Science, Entrepreneurship, Marketing

      4.6

      (69 reviews)

      Beginner · Specialization · 3-6 Months

    Searches related to statistics for data science

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    In summary, here are 10 of our most popular statistics for data science courses

    • Understanding and Visualizing Data with Python: University of Michigan
    • Microsoft Azure Data Scientist Associate (DP-100): Microsoft
    • Data Science Foundations: Data Structures and Algorithms: University of Colorado Boulder
    • TensorFlow 2 for Deep Learning: Imperial College London
    • Statistical Modeling for Data Science Applications: University of Colorado Boulder
    • IBM Data Science: IBM Skills Network
    • Advanced Linear Models for Data Science 1: Least Squares: Johns Hopkins University
    • Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
    • Python for Data Science, AI & Development: IBM Skills Network
    • AI for Medicine: DeepLearning.AI

    Frequently Asked Questions about Statistics For Data Science

    • Statistics for data science refers to the mathematical analysis used to sort, analyze, interpret, and present data. It includes concepts like probability distribution, regression, and over or under-sampling. Descriptive statistics organizes data based on characteristics of the data set, such as normal distribution, central tendency, variability, and standard deviation. Inferential statistics incorporates the use of probability theory to infer characteristics of the data set.‎

    • Learning statistics for data science can lead to career opportunities in data science and related fields. As organizations increasingly rely on data to make decisions, they tend to seek out analysts who understand how to work with data and present it to stakeholders. Learning statistics for data science can also provide a good salary. As of 2020, the median pay for computer and information research scientists in the US is $122,840 and the job market remains positive, according to the Bureau of Labor Statistics. Mathematicians and statisticians have a similar job outlook and a median salary of $92,030 per year.‎

    • Data analysis, data architects, data scientists, and information officers typically use statistics for data science in their regular work. Data science is a broad field, and statistics can be useful in other roles that require analyzing and presenting data. This includes data warehouse analysts, data visualization developers, database managers, and machine learning engineers. Additional related fields include financial analysts, teachers, and researchers working for universities and corporate settings.‎

    • Through online courses, you can learn the fundamentals of statistics for data science, including the theories and techniques statisticians use in their work. Some courses explore fundamental concepts like Bayes’ Theorem and probability theory. Others present methods for calculating and evaluating data sets. You can brush up on your knowledge of programs statisticians use, like Excel and Python, or examine the application of statistics specific fields.‎

    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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