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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
      S

      Stanford University

      Organizational Analysis

      Skills you'll gain: Organizational Structure, Decision Making, Organizational Leadership, Organizational Change, Professional Networking, Strategic Decision-Making, Business, Social Sciences, Culture, Sociology, Analysis, Resource Management, Learning Theory, Innovation, Negotiation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      B

      Berklee

      Writing and Producing Music in Your Home Studio

      Skills you'll gain: Music, Musical Composition, Music Theory, Peer Review, Music Performance, Active Listening, Storytelling, Post-Production, Constructive Feedback, Editing, Creativity, Performing Arts, Media Production, Writing, Performance Tuning, Self-Awareness

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • V

      Vanderbilt University

      Advanced Prompt Engineering for Everyone

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, Large Language Modeling, Artificial Intelligence, Data Quality

      4.9
      Rating, 4.9 out of 5 stars
      ·
      271 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California San Diego

      Interaction Design

      Skills you'll gain: Design Research, Interaction Design, User Experience Design, Statistical Analysis, Usability, Ideation, User Research, Graphic and Visual Design, User Interface (UI) Design, Experimentation, Prototyping, Human Centered Design, A/B Testing, Usability Testing, User Centered Design, Mockups, Human Computer Interaction, Human Factors, Collaborative Software, Telecommuting

      4.5
      Rating, 4.5 out of 5 stars
      ·
      4K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Marketing in a Digital World

      Skills you'll gain: Digital Marketing, Marketing, Marketing Strategies, MarTech, Digital Advertising, Digital Transformation, E-Commerce, Price Negotiation, Consumer Behaviour, Product Development, Product Promotion, Innovation, Customer Engagement

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      17K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Data Mining Methods

      Skills you'll gain: Data Mining, Anomaly Detection, Unsupervised Learning, Supervised Learning, Big Data, Unstructured Data, Data Science, Machine Learning Algorithms, Exploratory Data Analysis, Classification And Regression Tree (CART), Data Analysis, Analysis, Statistical Analysis, Machine Learning, Algorithms, Time Series Analysis and Forecasting, Bayesian Statistics, Artificial Neural Networks

      Build toward a degree

      4.3
      Rating, 4.3 out of 5 stars
      ·
      57 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      Università di Napoli Federico II

      Global Politics

      Skills you'll gain: International Relations, Political Sciences, Social Sciences, World History, Governance, Cultural Diversity, Research Methodologies, Economics, Environment and Resource Management, Security Strategy

      4.4
      Rating, 4.4 out of 5 stars
      ·
      47 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      D

      DeepLearning.AI

      Data Analytics Foundations

      Skills you'll gain: Data Storytelling, Google Sheets, Data Visualization, Spreadsheet Software, Large Language Modeling, Data Literacy, Data Presentation, Data Visualization Software, Business Analysis, Data Analysis, Analytics, Business Requirements, Exploratory Data Analysis, Data-Driven Decision-Making, Stakeholder Engagement

      4.7
      Rating, 4.7 out of 5 stars
      ·
      63 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Python for Beginners: Variables and Strings

      Skills you'll gain: Data Import/Export, Programming Principles, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      49 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • D

      DeepLearning.AI

      Natural Language Processing with Classification and Vector Spaces

      Skills you'll gain: Natural Language Processing, Supervised Learning, Dimensionality Reduction, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Tensorflow, Linear Algebra, Probability & Statistics

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

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Regression and Classification

      Skills you'll gain: Statistical Modeling, Statistical Machine Learning, Data Science, Statistical Methods, Classification And Regression Tree (CART), Statistical Analysis, Regression Analysis, Predictive Modeling, Statistical Inference, Applied Machine Learning, Supervised Learning, Unsupervised Learning, Machine Learning Algorithms

      Build toward a degree

      3.9
      Rating, 3.9 out of 5 stars
      ·
      14 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      IBM Program Manager

      Skills you'll gain: Program Management, Stakeholder Management, Resource Allocation, Agile Software Development, Stakeholder Engagement, Agile Methodology, Project Management Life Cycle, Kanban Principles, Change Management, Project Management Office (PMO), Organizational Strategy, Agile Project Management, Risk Management, Resource Management, Governance, Earned Value Management, Cost Management, Team Building, Project Management, Generative AI Agents

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.5K reviews

      Beginner · Professional Certificate · 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

    • Organizational Analysis : Stanford University
    • Writing and Producing Music in Your Home Studio: Berklee
    • Advanced Prompt Engineering for Everyone: Vanderbilt University
    • Interaction Design: University of California San Diego
    • Marketing in a Digital World: University of Illinois Urbana-Champaign
    • Data Mining Methods: University of Colorado Boulder
    • Global Politics: Università di Napoli Federico II
    • Data Analytics Foundations: DeepLearning.AI
    • Python for Beginners: Variables and Strings: Coursera Project Network
    • Natural Language Processing with Classification and Vector Spaces: 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.‎

    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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