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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 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

    • 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, SQL, Generative AI, 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

      Introduction to Data Science

      Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Peer Review, Data Modeling, Databases, Stored Procedure, Relational Databases, Database Design, Query Languages, Data Science, Database Management, Big Data, Computer Programming Tools, Data Analysis Software, Data Cleansing, GitHub, Cloud Computing, Data Analysis

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      98K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado System

      Clinical Data Science

      Skills you'll gain: Tidyverse (R Package), Clinical Data Management, Extract, Transform, Load, Data Modeling, Clinical Research, R Programming, Data Manipulation, Predictive Modeling, Database Design, Google Cloud Platform, Intensive Care Unit, Data Ethics, Data Quality, Risk Modeling, Natural Language Processing, Health Informatics, Statistical Modeling, Bioinformatics, Text Mining, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      468 reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Data Management

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Data Governance, Data Security, Data Migration, Database Design, Data Literacy, Descriptive Statistics, Extract, Transform, Load, Data Mining, Cloud Storage, Data Visualization Software, Data Store, IBM DB2, Data Management, Relational Databases, MySQL, Excel Formulas

      4.7
      Rating, 4.7 out of 5 stars
      ·
      16K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Data Analysis and Visualization Foundations

      Skills you'll gain: Data Storytelling, Big Data, Data Visualization Software, Data Analysis, Dashboard, IBM Cognos Analytics, Statistical Analysis, Data Mining, Apache Hadoop, Tree Maps, Excel Formulas, Apache Hive, Microsoft Excel, Data Warehousing, Data Quality, Data Cleansing, Scatter Plots, Apache Spark, Pivot Tables And Charts, Data Import/Export

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      27K reviews

      Beginner · Specialization · 3 - 6 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

    • I

      IBM

      IBM AI Foundations for Business

      Skills you'll gain: Large Language Modeling, Data Literacy, Data Mining, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Information Architecture, Strategic Decision-Making, Enterprise Architecture, Cloud Computing, Applied Machine Learning, Data Analysis, Data Science, Deep Learning, Digital Transformation, Data Strategy, Business Strategy, Business Process Automation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      93K reviews

      Beginner · Specialization · 1 - 3 Months

    • I

      IBM

      AI Foundations for Everyone

      Skills you'll gain: Prompt Engineering, ChatGPT, Large Language Modeling, Generative AI, Artificial Intelligence, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), OpenAI, IBM Cloud, Private Cloud, Data Loss Prevention, Applied Machine Learning, Deep Learning, WordPress, Artificial Neural Networks, Governance, Machine Learning, Generative AI Agents, Automation, Digital Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      26K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Linear Algebra for Machine Learning and Data Science

      Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Machine Learning Methods, Jupyter, Data Manipulation, Data Science, Applied Mathematics, Python Programming, Image Analysis, Artificial Intelligence

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

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: AI skills
      AI skills
      D

      DeepLearning.AI

      DeepLearning.AI Data Analytics

      Skills you'll gain: Data Storytelling, Google Sheets, Data Visualization, Data Presentation, Spreadsheet Software, Large Language Modeling, Dashboard, Pandas (Python Package), Web Scraping, Interactive Data Visualization, Time Series Analysis and Forecasting, Probability & Statistics, Statistical Analysis, Statistics, Statistical Modeling, Matplotlib, Data Visualization Software, SQL, Databases, Data Ethics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      55 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • J

      Johns Hopkins University

      Python for Genomic Data Science

      Skills you'll gain: Bioinformatics, Data Structures, Jupyter, Python Programming, Programming Principles, Scripting Languages, Scripting, Data Processing, Computer Programming, Data Manipulation, File Management

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 4 Weeks

    Statistics For Data Science learners also search

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    1…789…834

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

    • Introduction to Data Science in Python: University of Michigan
    • IBM Data Analyst: IBM
    • Introduction to Data Science: IBM
    • Clinical Data Science: University of Colorado System
    • IBM Data Management: IBM
    • Data Analysis and Visualization Foundations: IBM
    • Preparing for Google Cloud Certification: Cloud Data Engineer: Google Cloud
    • IBM AI Foundations for Business: IBM
    • AI Foundations for Everyone: IBM
    • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI

    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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