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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

      What is Data Science?

      Skills you'll gain: Data Literacy, Data Mining, Big Data, Cloud Computing, Data Analysis, Data Science, Digital Transformation, Data-Driven Decision-Making, Deep Learning, Machine Learning, Artificial Intelligence

      4.7
      Rating, 4.7 out of 5 stars
      ·
      75K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California, Irvine

      Data Science Fundamentals

      Skills you'll gain: Data Ethics, Predictive Modeling, Unsupervised Learning, Natural Language Processing, Predictive Analytics, Data Analysis, Classification And Regression Tree (CART), Regression Analysis, Data Mining, Statistical Analysis, Data Science, Social Media, Text Mining, Anomaly Detection, Business Analytics, Decision Tree Learning, Statistical Modeling, Big Data, Analytics, Cloud Computing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      239 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, Statistical Inference, Social Sciences, Statistical Methods, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Excel Basics for Data Analysis

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Analysis, Data Import/Export, Spreadsheet Software, Data Wrangling, Data Quality, Pivot Tables And Charts, Google Sheets, Data Manipulation, Data Visualization Software, Information Privacy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      9.6K reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google

      Google Advanced Data Analytics

      Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Statistical Hypothesis Testing, Data Ethics, Data Presentation, Data Visualization Software, Sampling (Statistics), Regression Analysis, Feature Engineering, Data Transformation, Descriptive Statistics, Data Visualization, Tableau Software, Data Manipulation, Statistical Analysis, Probability Distribution, Statistical Methods, Applied Machine Learning, Object Oriented Programming (OOP), Data Analysis

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.1K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Data Analysis with Python

      Skills you'll gain: Data Wrangling, Data Cleansing, Data Analysis, Data Manipulation, Data Import/Export, Exploratory Data Analysis, Data Science, Statistical Analysis, Descriptive Statistics, Regression Analysis, Predictive Modeling, Pandas (Python Package), Scikit Learn (Machine Learning Library), Machine Learning Methods, Data Pipelines, NumPy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud Data Engineer

      Skills you'll gain: Data Pipelines, Dataflow, Google Cloud Platform, Real Time Data, Data Maintenance, Data Lakes, Data Storage, MLOps (Machine Learning Operations), Data Analysis, Dashboard, Data Warehousing, Data Processing, Extract, Transform, Load, Cloud Engineering, Data Infrastructure, Cloud Infrastructure, Cloud Storage, Big Data, Tensorflow, Unstructured Data

      4.6
      Rating, 4.6 out of 5 stars
      ·
      19K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: AI skills
      AI skills
      M

      Microsoft

      Microsoft Power BI Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Excel Formulas, Extract, Transform, Load, Power BI, Data Analysis Expressions (DAX), Microsoft Excel, Microsoft Copilot, Data Modeling, Data-Driven Decision-Making, Star Schema, Data Analysis, Data Presentation, Data Visualization Software, Spreadsheet Software, Data Validation, Interactive Data Visualization, Data Transformation, Data Cleansing, Data Storage

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.2K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Michigan

      Applied Data Science with Python

      Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Data Visualization Software, Interactive Data Visualization, Scientific Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Visualization (Computer Graphics), Statistical Visualization, Scikit Learn (Machine Learning Library), Network Model, Jupyter, NumPy, Graph Theory, Data Manipulation, Natural Language Processing, Data Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      34K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Engineering

      Skills you'll gain: NoSQL, Data Warehousing, SQL, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, 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

    • U

      University of California San Diego

      Data Structures and Algorithms

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Network Routing, Program Development, Debugging, Network Model, Bioinformatics, Operations Research, Data Storage, Development Testing, Test Engineering, Software Testing, Theoretical Computer Science, Computational Thinking, Network Analysis, Test Case, Programming Principles, Computer Programming, Epidemiology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      17K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Tools for Data Science

      Skills you'll gain: Jupyter, Computer Programming Tools, Data Analysis Software, Data Visualization Software, Data Science, GitHub, Big Data, R Programming, Statistical Programming, Application Programming Interface (API), Machine Learning, Cloud Computing, Git (Version Control System), Development Environment, Other Programming Languages, Query Languages

      4.5
      Rating, 4.5 out of 5 stars
      ·
      30K reviews

      Beginner · Course · 1 - 3 Months

    Statistics For Data Science learners also search

    Statistics for Data Analysis
    Statistics
    R Statistics
    Python for Statistics
    Data Modeling
    Applied Statistics
    Beginner Statistics
    Statistics Projects
    1…456…834

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

    • What is Data Science? : IBM
    • Data Science Fundamentals: University of California, Irvine
    • Methods and Statistics in Social Sciences: University of Amsterdam
    • Excel Basics for Data Analysis: IBM
    • Google Advanced Data Analytics: Google
    • Data Analysis with Python: IBM
    • Preparing for Google Cloud Certification: Cloud Data Engineer: Google Cloud
    • Microsoft Power BI Data Analyst: Microsoft
    • Applied Data Science with Python: University of Michigan
    • IBM Data Engineering: 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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