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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

      Imperial College London

      Mathematics for Machine Learning: Multivariate Calculus

      Skills you'll gain: Regression Analysis, Calculus, Advanced Mathematics, Machine Learning Algorithms, Statistical Analysis, Linear Algebra, Artificial Neural Networks, Python Programming, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Data Mining Foundations and Practice

      Skills you'll gain: Data Mining, Unsupervised Learning, Data Warehousing, Data Pipelines, Data Processing, Data Integration, Data Modeling, Data Science, Data Cleansing, Big Data, Supervised Learning, Data Transformation, Machine Learning Methods, Text Mining, Data Quality, Classification And Regression Tree (CART), Unstructured Data, Data Analysis, Data Presentation, Exploratory Data Analysis

      Build toward a degree

      4.1
      Rating, 4.1 out of 5 stars
      ·
      134 reviews

      Intermediate · Specialization · 1 - 3 Months

    • D

      DeepLearning.AI

      AI Python for Beginners

      Skills you'll gain: Large Language Modeling, Prompt Engineering, Artificial Intelligence, Jupyter, Python Programming, Data Analysis, ChatGPT, Application Development, Generative AI, Scripting, Automation, Computer Programming, Application Programming Interface (API)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      112 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      M

      Meta

      Python Data Analytics

      Skills you'll gain: Pandas (Python Package), Data Analysis, Exploratory Data Analysis, Data Modeling, Data Manipulation, Jupyter, Data Processing, Matplotlib, Programming Principles, Data Cleansing, Data Visualization Software, Python Programming, Scripting

      4.3
      Rating, 4.3 out of 5 stars
      ·
      199 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Davis

      Learn Spanish: Basic Spanish Vocabulary

      Skills you'll gain: Peer Review, Language Learning, Spanish Language, Oral Expression, Grammar, Oral Comprehension, Vocabulary, Culture, Writing, Writing and Editing, Research, Literacy

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

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Alberta

      Indigenous Canada

      Skills you'll gain: Art History, Social Studies, Storytelling, Cultural Diversity, Culture, Social Justice, Intercultural Competence, Socioeconomics, World History, Political Sciences, Social Sciences, Community Development, Land Management, Governance

      4.8
      Rating, 4.8 out of 5 stars
      ·
      23K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      ChatGPT Advanced Data Analysis

      Skills you'll gain: Prompt Engineering, Data Presentation, ChatGPT, Document Management, Artificial Intelligence, Microsoft Excel, Problem Solving, Data Analysis, Generative AI, Information Management, File Management, Creativity, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      785 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Virginia

      Leading the Modern Day Business

      Skills you'll gain: Design Thinking, Digital Transformation, Creative Problem-Solving, New Product Development, Ideation, Business Transformation, Product Management, Innovation, Creativity, Product Lifecycle Management, Strategic Thinking, Product Improvement, Market Opportunities, Technology Strategies, Information Technology, Customer Insights, Corporate Strategy, Business Strategy, Process Design, Large Language Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      20K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Full-Stack JavaScript Developer

      Skills you'll gain: Istio, HTML and CSS, Node.JS, Software Development Life Cycle, Software Architecture, Server Side, MongoDB, Application Deployment, CI/CD, Cloud-Native Computing, React Redux, NoSQL, Kubernetes, Restful API, OpenShift, Git (Version Control System), Cloud Applications, Containerization, Ajax, Interviewing Skills

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • 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

    • U

      University of Pennsylvania

      Philosophy of Science

      Skills you'll gain: Scientific Methods, Science and Research, Research, Experimentation, Research Methodologies, Policy Analysis, Peer Review, Social Sciences, Simulations, Ethical Standards And Conduct

      4.7
      Rating, 4.7 out of 5 stars
      ·
      240 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Introduction to Generative AI Learning Path

      Skills you'll gain: Large Language Modeling, Generative AI, Prompt Engineering, Data Ethics, Google Cloud Platform, Business Ethics, Application Development, Artificial Intelligence, Accountability, Compliance Training, Ethical Standards And Conduct, Artificial Intelligence and Machine Learning (AI/ML), Governance, Organizational Effectiveness, Machine Learning Methods, Decision Making, Corporate Strategy

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.2K reviews

      Intermediate · Specialization · 1 - 3 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

    • Mathematics for Machine Learning: Multivariate Calculus: Imperial College London
    • Data Mining Foundations and Practice: University of Colorado Boulder
    • AI Python for Beginners: DeepLearning.AI
    • Python Data Analytics: Meta
    • Learn Spanish: Basic Spanish Vocabulary: University of California, Davis
    • Indigenous Canada: University of Alberta
    • ChatGPT Advanced Data Analysis: Vanderbilt University
    • Leading the Modern Day Business: University of Virginia
    • IBM Full-Stack JavaScript Developer: IBM
    • Finance for Non-Financial Professionals: University of California, Irvine

    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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