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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: AI skills
      AI skills
      I

      IBM

      IBM Data Engineering

      Skills you'll gain: NoSQL, Data Warehousing, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, SQL, IBM Cognos Analytics, MySQL, Apache Spark, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Data Store, Jupyter, Generative AI, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • D

      Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google

      Foundations of Data Science

      Skills you'll gain: Data Storytelling, Data Ethics, Data Presentation, Data Analysis, Data-Driven Decision-Making, Analytical Skills, Data Science, Project Design, Communication, Business, Business Ethics, Business Workflow Analysis, Stakeholder Communications, Professional Networking, Data Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.1K reviews

      Advanced · Course · 1 - 3 Months

    • M

      Macquarie University

      Excel Skills for Business

      Skills you'll gain: Microsoft Excel, Dashboard, Excel Formulas, Spreadsheet Software, Data Visualization, Excel Macros, Data Validation, Data Analysis Expressions (DAX), Data Cleansing, Data Modeling, Financial Forecasting, Predictive Modeling, Financial Modeling, Workflow Management, Finance, Data Management, Business Intelligence Software, Consolidation, Data Integrity, Data Entry

      4.9
      Rating, 4.9 out of 5 stars
      ·
      62K reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      Macquarie University

      Excel Skills for Data Analytics and Visualization

      Skills you'll gain: Pivot Tables And Charts, Data Storytelling, Power BI, Excel Formulas, Data Analysis Expressions (DAX), Data Visualization Software, Interactive Data Visualization, Microsoft Excel, Spreadsheet Software, Dashboard, Data Modeling, Data Cleansing, Data Manipulation, Excel Macros, Infographics, Data Transformation, Data Analysis Software, Data Validation, Data Analysis, Microsoft Power Platform

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Applied Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Interactive Data Visualization, Exploratory Data Analysis, Data Cleansing, Jupyter, Matplotlib, Data Analysis, Pandas (Python Package), Data Manipulation, Seaborn, Data Import/Export, Predictive Modeling, Web Scraping, Automation, Data Science, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Amsterdam

      Methods and Statistics in Social Sciences

      Skills you'll gain: Qualitative Research, Scientific Methods, Descriptive Statistics, Statistical Analysis, Statistical Hypothesis Testing, Research, Sampling (Statistics), Probability Distribution, Correlation Analysis, Research Design, Research Reports, Science and Research, Interviewing Skills, Data Analysis, Probability, Data Collection, Social Sciences, Statistical Methods, Probability & Statistics, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Generative AI, SQL, Interactive Data Visualization, Exploratory Data Analysis, Data Cleansing, Big Data, Jupyter, Matplotlib, Data Analysis, Statistical Analysis, Pandas (Python Package), Data Manipulation, Excel Formulas, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      91K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Generative AI for Data Analysts

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, Data Storytelling, OpenAI, Analytics, Data Analysis, Artificial Intelligence and Machine Learning (AI/ML), Dashboard, Large Language Modeling, Data Ethics, Artificial Intelligence, Program Development, Data Visualization Software, SQL, Python Programming, Query Languages, Image Analysis, Content Creation, Virtual Environment

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

      Intermediate · Specialization · 1 - 3 Months

    • U

      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles

      4.5
      Rating, 4.5 out of 5 stars
      ·
      27K reviews

      Intermediate · Course · 1 - 4 Weeks

    • D
      A

      Multiple educators

      DeepLearning.AI Data Engineering

      Skills you'll gain: Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Storage Technologies, Data Architecture, Data Transformation, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Apache Hadoop, Extract, Transform, Load, Data Lakes, Amazon Web Services, Apache Spark, Database Systems, Data Integration, Infrastructure as Code (IaC), Terraform

      4.8
      Rating, 4.8 out of 5 stars
      ·
      432 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • U

      University of California, Santa Cruz

      Bayesian Statistics

      Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Analysis, Probability, Statistical Machine Learning, Statistical Methods, Statistical Analysis, Advanced Analytics, Mathematical Modeling, Microsoft Excel, Markov Model, Probability Distribution, Probability & Statistics, Unsupervised Learning, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    Statistics For Data Science learners also search

    Statistics for Data Analysis
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    1…567…834

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

    • IBM Data Engineering: IBM
    • Data Analysis with R: Duke University
    • Foundations of Data Science: Google
    • Excel Skills for Business: Macquarie University
    • Excel Skills for Data Analytics and Visualization: Macquarie University
    • Applied Data Science: IBM
    • Methods and Statistics in Social Sciences: University of Amsterdam
    • IBM Data Analyst: IBM
    • Generative AI for Data Analysts: IBM
    • Introduction to Data Science in Python: University of Michigan

    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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