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    • Statistics For Data Science

    Statistics for Data Science Courses Online

    Master statistics for data science applications. Learn about statistical techniques, data analysis, and machine learning models.

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    Explore the Statistics for Data Science Course Catalog

    • U

      University of Michigan

      Using Databases with Python

      Skills you'll gain: Relational Databases, Database Design, SQL, Databases, Web Scraping, Data Modeling, Database Management, Data Visualization Software, Object-Relational Mapping, Object Oriented Programming (OOP), Data Processing, Python Programming, Application Programming Interface (API)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      21K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California San Diego

      Object Oriented Java Programming: Data Structures and Beyond

      Skills you'll gain: Unit Testing, Growth Mindedness, Data Structures, Graph Theory, Event-Driven Programming, Interactive Data Visualization, Java, Network Analysis, Object Oriented Programming (OOP), Technical Communication, Development Testing, User Interface (UI), Java Programming, Software Testing, Computer Programming, Adaptability, Object Oriented Design, Performance Tuning, Algorithms, Software Design

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Pennsylvania

      Introduction to Financial Accounting

      Skills you'll gain: Financial Statements, Financial Statement Analysis, Financial Reporting, Financial Accounting, Balance Sheet, Accrual Accounting, Financial Analysis, Cash Flows, Income Statement, Bookkeeping, Revenue Recognition, Depreciation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      8.3K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Resampling, Selection and Splines

      Skills you'll gain: Data Science, R Programming, Statistical Machine Learning, Advanced Analytics, Dimensionality Reduction, Statistical Modeling, Statistical Analysis, Statistical Methods, Sampling (Statistics), Regression Analysis, Statistical Inference

      5
      Rating, 5 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Michigan

      Applied Plotting, Charting & Data Representation in Python

      Skills you'll gain: Matplotlib, Data Visualization Software, Interactive Data Visualization, Scientific Visualization, Visualization (Computer Graphics), Statistical Visualization, Data Presentation, Graphing, Scatter Plots, Data Manipulation, Histogram, NumPy, Pandas (Python Package)

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google

      Build Wireframes and Low-Fidelity Prototypes

      Skills you'll gain: Storyboarding, Wireframing, Figma (Design Software), Information Architecture, User Story, User Experience Design, User Centered Design, Prototyping, Usability, User Interface and User Experience (UI/UX) Design, Mockups, User Flows

      4.9
      Rating, 4.9 out of 5 stars
      ·
      9.3K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      T

      The University of Edinburgh

      Code Yourself! An Introduction to Programming

      Skills you'll gain: Software Engineering, Video Game Development, Software Testing, Software Development, Programming Principles, Software Design, Game Design, Computer Programming, Animation and Game Design, Debugging, Computational Thinking, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Business Writing

      Skills you'll gain: Business Writing, Business Correspondence, Business Communication, Writing, Organizational Skills, Concision, Writing and Editing, Proofreading, Grammar, Communication, Editing, Organizational Strategy, Persuasive Communication, Verbal Communication Skills, Communication Strategies

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

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Getting and Cleaning Data

      Skills you'll gain: Data Manipulation, Data Cleansing, Data Wrangling, Data Integration, Data Quality, Data Transformation, Data Import/Export, Data Collection, Data Management, Web Scraping, Data Access, R Programming, Exploratory Data Analysis, MySQL, File Management, SQL, Application Programming Interface (API)

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Epidemiology in Public Health Practice

      Skills you'll gain: Epidemiology, Public Health, Spatial Data Analysis, Data Presentation, Public Health and Disease Prevention, Geographic Information Systems, Health Policy, Chronic Diseases, Health Systems, Infectious Diseases, Biostatistics, Risk Analysis, Investigation, Community Health, Health Care, Data Analysis, Program Evaluation, Health Information Management, Health Informatics, Continuous Monitoring

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • V

      Vanderbilt University

      Introduction to Programming with MATLAB

      Skills you'll gain: Matlab, Computer Programming, Programming Principles, UI Components, Software Design, Debugging, Mathematical Software, Development Environment, Computer Science, File Management, Algorithms, Data Import/Export, Data Structures, Engineering Calculations, Plot (Graphics), Data Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18K reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      Java Programming: Solving Problems with Software

      Skills you'll gain: Debugging, Java, Algorithms, Statistical Analysis, Software Design, Computer Programming, Integrated Development Environments, Data Processing, Object Oriented Programming (OOP), Data Analysis, Software Testing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8K reviews

      Beginner · Course · 1 - 3 Months

    Statistics For Data Science learners also search

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    1…525354…834

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

    • Using Databases with Python: University of Michigan
    • Object Oriented Java Programming: Data Structures and Beyond: University of California San Diego
    • Introduction to Financial Accounting: University of Pennsylvania
    • Resampling, Selection and Splines: University of Colorado Boulder
    • Applied Plotting, Charting & Data Representation in Python: University of Michigan
    • Build Wireframes and Low-Fidelity Prototypes: Google
    • Code Yourself! An Introduction to Programming: The University of Edinburgh
    • Business Writing: University of Colorado Boulder
    • Getting and Cleaning Data: Johns Hopkins University
    • Epidemiology in Public Health Practice: Johns Hopkins University

    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.‎

    Online Statistics for Data Science courses offer a convenient and flexible way to enhance your knowledge or learn new Statistics for Data Science skills. Choose from a wide range of Statistics for Data Science courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Statistics for Data Science, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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