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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
      Free
      Y

      Yale University

      Managing Emotions in Times of Uncertainty & Stress

      Skills you'll gain: Student Support and Services, Working With Children, Emotional Intelligence, School Counseling, Personal Development, Stress Management, Classroom Management, Cultural Responsiveness, Empathy, Self-Awareness, Resilience, Relationship Building

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      P

      Peking University

      Chinese for HSK 4

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

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      Cybersecurity Fundamentals

      Skills you'll gain: Encryption, Identity and Access Management, Public Key Infrastructure, Endpoint Security, Cryptography, Network Security, Cybersecurity, Threat Detection, Cyber Attacks, Cryptographic Protocols, Data Security, Email Security, Computer Security Awareness Training, Advanced Encryption Standard (AES), Security Awareness, Secure Coding, Data Encryption Standard, Technical Support and Services, Information Technology, Cyber Security Strategy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      Universidade de São Paulo

      Introdução à Ciência da Computação com Python Parte 1

      Skills you'll gain: Debugging, Computational Thinking, Programming Principles, Data Structures, Computer Programming, Program Development, Integrated Development Environments, Computer Science, Python Programming, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      7.4K reviews

      Beginner · Course · 1 - 3 Months

    • B

      Berklee

      The Singer Songwriter

      Skills you'll gain: Music Theory, File Management, Music, Music Performance, Musical Composition, Peer Review, Instrumental Music, Self-Awareness, Performing Arts, Creativity, Automation, Storytelling, Writing, Editing, Software Installation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      G

      Georgia Institute of Technology

      Introduction to Engineering Mechanics

      Skills you'll gain: Engineering Analysis, Mechanics, Torque (Physics), Engineering Calculations, Mechanical Engineering, Engineering, Civil Engineering, Structural Analysis, Trigonometry

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.1K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Fintech: Foundations & Applications of Financial Technology

      Skills you'll gain: FinTech, Portfolio Management, Consumer Lending, Return On Investment, Blockchain, Cryptography, Credit/Debit Card Processing, Digital Assets, Financial Services, Payment Processing, Investments, Lending and Underwriting, Investment Management, Technology Strategies, Emerging Technologies, Risk Analysis, Fundraising and Crowdsourcing, Financial Market, Market Analysis, Artificial Intelligence and Machine Learning (AI/ML)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      Duke University

      Linear Regression and Modeling

      Skills you'll gain: Regression Analysis, Data Analysis Software, Statistical Analysis, R Programming, Statistical Modeling, Statistical Inference, Correlation Analysis, Statistical Methods, Exploratory Data Analysis, Mathematical Modeling, Predictive Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • S

      SAP

      SAP Technology Consultant

      Skills you'll gain: Digital Transformation, Cloud Computing Architecture, Stakeholder Engagement, Consulting, Systems Design, Relationship Management, Business Consulting, Cloud Computing, Technical Design, Solution Design, User Feedback, Product Strategy, Technical Consulting, Customer Engagement, Cybersecurity, System Implementation, Professional Networking, Project Management, SAP Applications, Test Planning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • A

      Arizona State University

      TESOL Certificate, Part 2: Teach English Now!

      Skills you'll gain: Oral Comprehension, Learning Management Systems, Education Software and Technology, Literacy, Grammar, Technology Strategies, English Language, Language Competency, End User Training and Support, Language Learning, Emerging Technologies, Vocabulary, Innovation, Digital Transformation, Organizational Skills

      4.9
      Rating, 4.9 out of 5 stars
      ·
      4.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • P

      Packt

      R Programming for Statistics and Data Science

      Skills you'll gain: R Programming, Exploratory Data Analysis, Statistical Hypothesis Testing, Ggplot2, Data Manipulation, Data Science, Tidyverse (R Package), Data Structures, Data Analysis, Statistical Analysis, Regression Analysis, Statistical Inference, Probability & Statistics, Data Transformation, Integrated Development Environments

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Machine Learning on Google Cloud

      Skills you'll gain: Feature Engineering, Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), MLOps (Machine Learning Operations), Cloud Infrastructure, Artificial Intelligence and Machine Learning (AI/ML), Data Pipelines, Dataflow, Cloud Platforms, Data Management, Data Governance, Workflow Management, Application Deployment, Deep Learning, Applied Machine Learning, Machine Learning, Predictive Modeling

      4.4
      Rating, 4.4 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    Statistics For Data Science learners also search

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

    • Managing Emotions in Times of Uncertainty & Stress: Yale University
    • Chinese for HSK 4: Peking University
    • Cybersecurity Fundamentals: IBM
    • Introdução à Ciência da Computação com Python Parte 1: Universidade de São Paulo
    • The Singer Songwriter: Berklee
    • Introduction to Engineering Mechanics: Georgia Institute of Technology
    • Fintech: Foundations & Applications of Financial Technology: University of Pennsylvania
    • Linear Regression and Modeling : Duke University
    • SAP Technology Consultant: SAP
    • TESOL Certificate, Part 2: Teach English Now!: Arizona State 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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