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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

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Warehouse Fundamentals

      Skills you'll gain: Data Warehousing, Extract, Transform, Load, Star Schema, IBM DB2, Data Modeling, Snowflake Schema, PostgreSQL, Database Design, Data Architecture, Data Mart, Database Systems, Data Lakes, Data Validation, Data Integration, SQL, Data Cleansing, Query Languages, Data Quality

      4.5
      Rating, 4.5 out of 5 stars
      ·
      229 reviews

      Intermediate · Course · 1 - 4 Weeks

    • F

      Fractal Analytics

      GenAI for Everyone

      Skills you'll gain: Generative AI, ChatGPT, Artificial Intelligence, Prompt Engineering, Operational Efficiency, Human Centered Design, Personalized Service, Ethical Standards And Conduct, Natural Language Processing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      411 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Finance for Non-Financial Professionals

      Skills you'll gain: Cash Management, Financial Analysis, Financial Statements, Budgeting, Accounting, Cash Flow Forecasting, Business Valuation, Financial Accounting, Finance, Financial Management, Balance Sheet

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.5K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      Start the UX Design Process: Empathize, Define, and Ideate

      Skills you'll gain: User Experience Design, User Story, Ideation, Usability, Web Content Accessibility Guidelines, User Research, Design Thinking, Human Centered Design, Competitive Analysis, User Flows, Persona Development

      4.8
      Rating, 4.8 out of 5 stars
      ·
      16K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Inferential Statistical Analysis with Python

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Statistical Inference, Statistics, Bayesian Statistics, Probability & Statistics, Statistical Analysis, Data Analysis, Jupyter, Python Programming, Matplotlib, NumPy

      4.6
      Rating, 4.6 out of 5 stars
      ·
      918 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Designing Effective Science Communication

      Skills you'll gain: Oral Expression, Human Learning, Education Software and Technology, Technical Communication, Education and Training, Writing, Learning Theory, Community Outreach, Pedagogy, Research, Technical Writing, Scientific Methods, Media and Communications, Science and Research, Persuasive Communication, Interviewing Skills, Photography, Infographics, Storytelling, Psychology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      123 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Washington

      Business English Communication Skills

      Skills you'll gain: Oral Expression, Negotiation, Proposal Writing, Presentations, Sales Presentation, Persuasive Communication, Event Planning, Business Writing, Peer Review, Business Communication, Taking Meeting Minutes, Public Speaking, Business Planning, Business Correspondence, Microsoft PowerPoint, Meeting Facilitation, Verbal Communication Skills, Professional Networking, English Language, Communication

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

      Intermediate · Specialization · 3 - 6 Months

    • Y

      Yonsei University

      Learn to Speak Korean 1

      Skills you'll gain: Language Competency, Language Learning, Vocabulary, Oral Comprehension, Grammar

      4.9
      Rating, 4.9 out of 5 stars
      ·
      12K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Probability Theory: Foundation for Data Science

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

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      253 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      O

      Olay

      Introduction to Cosmetic and Skincare Science

      Skills you'll gain: Product Testing, Laboratory Testing, Personal Care, Safety Assurance, Chemistry, Microbiology, Biology, Product Development, Regulatory Compliance, Innovation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      246 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM IT Project Manager

      Skills you'll gain: User Story, Software Development Life Cycle, Stakeholder Engagement, Project Management Life Cycle, Resource Management, Risk Management, Peer Review, Agile Software Development, Earned Value Management, Software Architecture, Development Environment, Stakeholder Management, Agile Methodology, Project Risk Management, Kanban Principles, Team Motivation, Information Technology, Sprint Retrospectives, Interviewing Skills, Project Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      8.5K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      M

      Meta

      Meta Back-End Developer

      Skills you'll gain: Django (Web Framework), Full-Stack Web Development, Version Control, Restful API, Data Structures, Unix Commands, Bootstrap (Front-End Framework), Git (Version Control System), Back-End Web Development, GitHub, Web Design and Development, Relational Databases, Front-End Web Development, Object Oriented Programming (OOP), Database Management Systems, SQL, Database Design, Unit Testing, Algorithms, Web Development

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

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

    • Data Warehouse Fundamentals: IBM
    • GenAI for Everyone: Fractal Analytics
    • Finance for Non-Financial Professionals: University of California, Irvine
    • Start the UX Design Process: Empathize, Define, and Ideate: Google
    • Inferential Statistical Analysis with Python: University of Michigan
    • Designing Effective Science Communication: University of Colorado Boulder
    • Business English Communication Skills: University of Washington
    • Learn to Speak Korean 1: Yonsei University
    • Probability Theory: Foundation for Data Science: University of Colorado Boulder
    • Introduction to Cosmetic and Skincare Science: Olay

    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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