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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

    • T

      The Hong Kong University of Science and Technology

      English for Effective Business Speaking

      Skills you'll gain: Sales Presentation, Interviewing Skills, Oral Expression, English Language, Business Communication, Presentations, Verbal Communication Skills, Business Writing, Grammar, Persuasive Communication, Communication, Public Speaking, Target Audience, Vocabulary, Professionalism, Communication Strategies

      4.5
      Rating, 4.5 out of 5 stars
      ·
      694 reviews

      Mixed · Course · 1 - 3 Months

    • C

      Columbia University

      Construction Management

      Skills you'll gain: Project Schedules, Construction Management, Construction Estimating, Project Finance, Cost Estimation, Punch Work, Project Risk Management, Bidding, Building Information Modeling, Scheduling, Cost Control, Environment Health And Safety, Project Closure, Lean Methodologies, Real Estate, Cash Flows, Construction, Business Transformation, Innovation, Architecture and Construction

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Pennsylvania

      Fundamentals of Quantitative Modeling

      Skills you'll gain: Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Financial Modeling, Business Mathematics, Markov Model, Probability, Predictive Analytics, Process Optimization, Risk Management, Statistics, Probability Distribution, Simulation and Simulation Software, Forecasting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of California, Santa Cruz

      Bayesian Statistics: Techniques and Models

      Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Markov Model, Statistical Analysis, Regression Analysis, R Programming, Simulations, Statistical Inference, Data Analysis, Probability, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      490 reviews

      Intermediate · Course · 1 - 3 Months

    • F

      Fractal Analytics

      Data Storytelling

      Skills you'll gain: Data Storytelling, Data Presentation, Data Visualization, Interactive Data Visualization, Storyboarding, Storytelling, Data Visualization Software, Infographics, Data Ethics, Data Literacy, Data-Driven Decision-Making, Data Analysis, Drive Engagement

      4.7
      Rating, 4.7 out of 5 stars
      ·
      109 reviews

      Beginner · Course · 1 - 4 Weeks

    • L

      LearnQuest

      Oracle SQL Databases

      Skills you'll gain: Oracle SQL Developer, SQL, Oracle Databases, PL/SQL, Database Design, Database Theory, Database Management Systems, Database Administration, Relational Databases, Database Management, Databases, Database Software, Database Architecture and Administration, Data Storage, Transaction Processing, Stored Procedure, Data Access, Data Modeling, Network Architecture, Data Integrity

      4.6
      Rating, 4.6 out of 5 stars
      ·
      850 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      University of California San Diego

      Biology Meets Programming: Bioinformatics for Beginners

      Skills you'll gain: Bioinformatics, Programming Principles, Molecular Biology, Python Programming, Computational Thinking, Biology, Algorithms, Data Structures

      4.2
      Rating, 4.2 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Virginia

      Business Strategy

      Skills you'll gain: Growth Strategies, Business Strategy, Strategic Thinking, Plan Execution, Mergers & Acquisitions, Competitive Analysis, Organizational Strategy, Business Ethics, Peer Review, Data-Driven Decision-Making, Corporate Strategy, Strategic Decision-Making, Governance, Stakeholder Management, New Business Development, Business Research, Analysis, Project Management, Innovation, Market Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California, Irvine

      Human Resources Analytics

      Skills you'll gain: Data Storytelling, Data-Driven Decision-Making, Training and Development, Performance Metric, Compensation Management, Human Resources Management and Planning, Human Resources, Human Resource Strategy, Workforce Planning, Business Metrics, Business Analytics, Employee Engagement, Recruitment, Talent Acquisition, Employee Retention

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2K reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      IBM

      GenAI for Executives & Business Leaders: An Introduction

      Skills you'll gain: Generative AI, Data Ethics, Artificial Intelligence, Business Transformation, Business Leadership, Business Ethics, Governance, Digital Transformation, Data-Driven Decision-Making, Business Strategies, Customer experience improvement, Customer Service

      4.7
      Rating, 4.7 out of 5 stars
      ·
      373 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      Financial Planning for Young Adults

      Skills you'll gain: Financial Planning, Investments, Budgeting, Risk Management, Goal Setting, Loans, Finance, Insurance, Credit Risk

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      I

      IBM

      Generative AI for Executives and Business Leaders

      Skills you'll gain: Prompt Engineering, Risk Mitigation, Generative AI, Risk Analysis, Feasibility Studies, Data Ethics, Brainstorming, Generative AI Agents, Business Priorities, Return On Investment, Data Strategy, Business Leadership, Goal Setting, Artificial Intelligence, Business Solutions, Ideation, Business Strategy, Scalability, Business Transformation, Business Ethics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      430 reviews

      Intermediate · Specialization · 1 - 4 Weeks

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

    • English for Effective Business Speaking: The Hong Kong University of Science and Technology
    • Construction Management: Columbia University
    • Fundamentals of Quantitative Modeling: University of Pennsylvania
    • Bayesian Statistics: Techniques and Models: University of California, Santa Cruz
    • Data Storytelling: Fractal Analytics
    • Oracle SQL Databases: LearnQuest
    • Biology Meets Programming: Bioinformatics for Beginners: University of California San Diego
    • Business Strategy: University of Virginia
    • Human Resources Analytics: University of California, Irvine
    • GenAI for Executives & Business Leaders: An Introduction: 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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