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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

    • I

      IBM

      SQL: A Practical Introduction for Querying Databases

      Skills you'll gain: SQL, MySQL, Microsoft SQL Servers, Relational Databases, Oracle Databases, Databases, Query Languages, IBM DB2, Database Management Systems, Stored Procedure, Cloud Applications, Data Analysis, Data Manipulation, Transaction Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      580 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      Computational Social Science

      Skills you'll gain: Network Analysis, Data Wrangling, Natural Language Processing, Web Scraping, Social Sciences, Data Ethics, Databases, Artificial Intelligence, Research, Simulations, Big Data, Systems Thinking, Data Science, Research Methodologies, Machine Learning, Data Collection, Computational Thinking, Economics, Policy, and Social Studies, Agentic systems, Data Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • V

      Vanderbilt University

      MATLAB Programming for Engineers and Scientists

      Skills you'll gain: Data Visualization, Image Analysis, Data Visualization Software, Matlab, Algorithms, Machine Learning Methods, User Interface (UI), Applied Machine Learning, Object Oriented Programming (OOP), Statistical Methods, Mathematical Software, Engineering Calculations, Data Analysis, Data Processing, Engineering Analysis, Computer Programming, Programming Principles, UI Components, Software Design, Debugging

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

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Generative AI for Everyone

      Skills you'll gain: Prompt Engineering, Generative AI, Large Language Modeling, OpenAI, ChatGPT, Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Business Process Automation, Automation, Ethical Standards And Conduct, Cloud Applications

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Generative AI for Product Managers

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI, Commercialization, Product Management, Product Lifecycle Management, Stakeholder Communications, OpenAI, Technical Product Management, Artificial Intelligence, Customer experience improvement, Team Building, Return On Investment, Product Development, New Product Development, Product Strategy, Microsoft Copilot, Large Language Modeling, Technical Communication, Program Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.3K reviews

      Intermediate · Specialization · 1 - 3 Months

    • G

      Google

      Ask Questions to Make Data-Driven Decisions

      Skills you'll gain: Spreadsheet Software, Stakeholder Communications, Dashboard, Data-Driven Decision-Making, Data Analysis, Analytical Skills, Data Presentation, Business Analysis, Expectation Management, Quantitative Research, Communication

      4.7
      Rating, 4.7 out of 5 stars
      ·
      34K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      University of California, Davis

      Materials Science: 10 Things Every Engineer Should Know

      Skills you'll gain: Semiconductors, Engineering, Mechanical Engineering, Failure Analysis, Manufacturing Processes, Structural Analysis, Engineering Analysis, Chemistry, Thermal Management, Electronics Engineering, Physical Science, Electronics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.5K reviews

      Mixed · Course · 1 - 3 Months

    • M

      Macquarie University

      Excel Power Tools for Data Analysis

      Skills you'll gain: Power BI, Data Analysis Expressions (DAX), Data Visualization Software, Data Modeling, Microsoft Excel, Interactive Data Visualization, Pivot Tables And Charts, Data Transformation, Dashboard, Data Manipulation, Data Analysis Software, Microsoft Power Platform, Data Import/Export, Data Cleansing

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

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      S

      Stanford University

      Child Nutrition and Cooking

      Skills you'll gain: Nutrition Education, Cooking, Nutrition and Diet, Food and Beverage, Food Safety and Sanitation, Child Health, Working With Children, Community Health, Parent Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      10K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      IBM Business Intelligence (BI) Analyst

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Database Design, MySQL, Presentations, Descriptive Statistics, Extract, Transform, Load, Business Intelligence, IBM DB2, Relational Databases, Tableau Software, Microsoft SQL Servers, Data Visualization Software, Interactive Data Visualization, Regression Analysis, Data-Driven Decision-Making, Excel Formulas, Microsoft Excel

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of London

      Mathematics for Computer Science

      Skills you'll gain: Graphing, Computational Thinking, Arithmetic, Applied Mathematics, Mathematical Modeling, General Mathematics, Computer Science, Computer Graphics, Systems Of Measurement, Cryptography

      4.1
      Rating, 4.1 out of 5 stars
      ·
      235 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      AI For Business

      Skills you'll gain: AI Personalization, Generative AI, Data Ethics, HR Tech, Data Governance, Big Data, Machine Learning, Personally Identifiable Information, Data Security, Governance, Business Strategy, Human Resources, Organizational Strategy, Customer Data Management, Credit Risk, Risk Management, Tensorflow, Personalized Service, Data-Driven Decision-Making, People Management

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

      Beginner · Specialization · 3 - 6 Months

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

    • SQL: A Practical Introduction for Querying Databases: IBM
    • Computational Social Science: University of California, Davis
    • MATLAB Programming for Engineers and Scientists: Vanderbilt University
    • Generative AI for Everyone: DeepLearning.AI
    • Generative AI for Product Managers: IBM
    • Ask Questions to Make Data-Driven Decisions: Google
    • Materials Science: 10 Things Every Engineer Should Know: University of California, Davis
    • Excel Power Tools for Data Analysis: Macquarie University
    • Child Nutrition and Cooking: Stanford University
    • IBM Business Intelligence (BI) Analyst: IBM

    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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