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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

    • U

      University of California, Davis

      JavaScript for Beginners

      Skills you'll gain: jQuery, Javascript and jQuery, Ajax, Javascript, Data Validation, UI Components, HTML and CSS, Scripting, JSON, Scripting Languages, JavaScript Frameworks, Web Applications, Event-Driven Programming, Web Development Tools, Web Development, Game Design, Application Development, Application Programming Interface (API), Object Oriented Programming (OOP), Animations

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      I

      Imperial College London

      Creative Thinking: Techniques and Tools for Success

      Skills you'll gain: Creative Thinking, Brainstorming, Creative Problem-Solving, Ideation, Creativity, Innovation, Curiosity, Critical Thinking, Problem Solving, Collaboration

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.8K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      Geographic Information Systems (GIS)

      Skills you'll gain: ArcGIS, GIS Software, Spatial Data Analysis, Spatial Analysis, Data Storytelling, Geographic Information Systems, Data Presentation, Data Sharing, Geospatial Mapping, Public Health, Land Management, Heat Maps, Metadata Management, Data Quality, Community Health, Data Mapping, Data Visualization Software, File Management, Network Analysis, Data Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      ETL and Data Pipelines with Shell, Airflow and Kafka

      Skills you'll gain: Extract, Transform, Load, Apache Airflow, Data Pipelines, Apache Kafka, Data Warehousing, Data Transformation, Data Migration, Web Scraping, Data Integration, Shell Script, Data Processing, Real Time Data, Data Cleansing, Big Data, Performance Tuning, Scalability

      4.5
      Rating, 4.5 out of 5 stars
      ·
      408 reviews

      Intermediate · Course · 1 - 3 Months

    • L

      LearnKartS

      Tableau for Data Visualization and Analysis

      Skills you'll gain: Tableau Software, Forecasting, Data Visualization Software, Dashboard, Interactive Data Visualization, Data Storytelling, Time Series Analysis and Forecasting, Trend Analysis, Data Modeling, Exploratory Data Analysis, Data Analysis, Geospatial Mapping, Data Integration, Systems Integration

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google

      Attract and Engage Customers with Digital Marketing

      Skills you'll gain: Search Engine Marketing, Search Engine Optimization, Google Ads, Online Advertising, Target Audience, Digital Marketing, Digital Advertising, Persona Development, Web Analytics and SEO, Keyword Research, Pay Per Click Advertising, Marketing, Customer Engagement, Customer Acquisition Management, Advertising, Marketing Strategies, Lead Generation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      7K reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Google Cloud Fundamentals: Core Infrastructure

      Skills you'll gain: Google Cloud Platform, Cloud Infrastructure, Prompt Engineering, Kubernetes, Containerization, Cloud Storage, Cloud Services, Identity and Access Management, Application Deployment, Virtual Machines, Cloud Computing, Application Development, Generative AI, Network Infrastructure, NoSQL, Scalability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      49K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      Fundamentals of Visualization with Tableau

      Skills you'll gain: Data Visualization Software, Data Visualization, Interactive Data Visualization, Dashboard, Tableau Software, Data Presentation, Tree Maps, Data Analysis, Data Import/Export

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California, Irvine

      Work Smarter, Not Harder: Time Management for Personal & Professional Productivity

      Skills you'll gain: Time Management, Planning, Delegation Skills, Productivity, Organizational Skills, Multitasking, Resource Management, Prioritization, Personal Development, Goal Setting, Professional Development, Communication

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Campus BBVA

      Business Analytics

      Skills you'll gain: Data Storytelling, Dashboard, Business Analytics, Data Quality, Business Intelligence, Data Analysis, Descriptive Statistics, Data-Driven Decision-Making, Probability & Statistics, Statistical Inference, Big Data, Exploratory Data Analysis, Project Management Life Cycle, Job Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      24 reviews

      Beginner · Course · 1 - 3 Months

    • R

      Rice University

      Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions

      Skills you'll gain: Descriptive Statistics, Probability & Statistics, Probability Distribution, Business Analytics, Microsoft Excel, Data Analysis, Statistical Analysis, Box Plots, Sampling (Statistics), Correlation Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.6K reviews

      Mixed · Course · 1 - 4 Weeks

    • T

      Tableau Learning Partner

      Data Visualization with Tableau

      Skills you'll gain: Data Visualization Software, Interactive Data Visualization, Tableau Software, Data Presentation, Tree Maps, Dashboard, Heat Maps, Geospatial Mapping, Data Storytelling, Data Manipulation, Data Mapping, Business Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      117 reviews

      Beginner · Course · 1 - 3 Months

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

    • JavaScript for Beginners: University of California, Davis
    • Creative Thinking: Techniques and Tools for Success: Imperial College London
    • Geographic Information Systems (GIS): University of California, Davis
    • ETL and Data Pipelines with Shell, Airflow and Kafka: IBM
    • Tableau for Data Visualization and Analysis: LearnKartS
    • Attract and Engage Customers with Digital Marketing: Google
    • Google Cloud Fundamentals: Core Infrastructure: Google Cloud
    • Fundamentals of Visualization with Tableau: University of California, Davis
    • Work Smarter, Not Harder: Time Management for Personal & Professional Productivity: University of California, Irvine
    • Business Analytics : Campus BBVA

    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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