What is 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.

Why learn statistics for data science?

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.

What are typical careers that use statistics for data science?

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.

How can online courses help me learn statistics for data science?

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.

What are the benefits of taking an online Statistics for Data Science course?

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.

What Statistics for Data Science courses are best for training and upskilling employees or the workforce?

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 .

Top Statistics For Data Science Courses - Learn Statistics For Data Science Online

Explore the Statistics for Data Science Course Catalog

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
6.5K reviews
Intermediate · Specialization · 1 - 3 Months
Johns Hopkins University
R Programming
Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Computer Programming Tools, Program Development, Data Structures, Performance Tuning, Data Import/Export
4.5
Rating, 4.5 out of 5 stars
22K reviews
Intermediate · Course · 1 - 4 Weeks
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
Google
Data Analysis with R Programming
Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Visualization, Data Analysis, Tidyverse (R Package), Data Visualization Software, Statistical Programming, Data Cleansing, Data Manipulation, Programming Principles, Data Transformation, Integrated Development Environments, Data Structures
4.8
Rating, 4.8 out of 5 stars
11K reviews
Beginner · Course · 1 - 3 Months
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
17K reviews
Beginner · Professional Certificate · 3 - 6 Months
IBM
Data Engineering Foundations
Skills you'll gain: Web Scraping, Database Design, SQL, MySQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Jupyter, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Manipulation, Stored Procedure, Databases, Automation, Python Programming
4.6
Rating, 4.6 out of 5 stars
56K reviews
Beginner · Specialization · 3 - 6 Months
Google Cloud
Data Engineering, Big Data, and Machine Learning on GCP
Skills you'll gain: Data Pipelines, Dataflow, Google Cloud Platform, Real Time Data, Data Lakes, MLOps (Machine Learning Operations), Dashboard, Data Warehousing, Extract, Transform, Load, Cloud Engineering, Data Infrastructure, Cloud Infrastructure, Cloud Storage, Big Data, Tensorflow, Unstructured Data, Data Integration, Data Migration, Data Processing, Data Visualization Software
4.6
Rating, 4.6 out of 5 stars
18K reviews
Intermediate · Specialization · 3 - 6 Months
University of California, Davis
Learn SQL Basics for Data Science
Skills you'll gain: Data Governance, Presentations, Data Cleansing, Feature Engineering, SQL, Apache Spark, A/B Testing, Distributed Computing, Descriptive Statistics, Data Lakes, Data Quality, Data Storytelling, Data Analysis, Peer Review, Exploratory Data Analysis, Data Manipulation, Data Pipelines, Databricks, Database Design, Query Languages
4.6
Rating, 4.6 out of 5 stars
18K reviews
Beginner · Specialization · 3 - 6 Months
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
Duke University
Introduction to Probability and Data with R
Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Software, Descriptive Statistics
4.7
Rating, 4.7 out of 5 stars
5.8K reviews
Beginner · Course · 1 - 3 Months
Status: New
IBM
IBM Data Architecture
Skills you'll gain: NoSQL, Data Warehousing, SQL, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Data Security, Linux Commands, Data Migration, Database Design, Data Governance, MySQL, Apache Spark, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Store
4.6
Rating, 4.6 out of 5 stars
6.6K reviews
Beginner · Professional Certificate · 3 - 6 Months
Google
Foundations: Data, Data, Everywhere
Skills you'll gain: Data Ethics, Data Analysis, Data-Driven Decision-Making, Google Sheets, Spreadsheet Software, Analytical Skills, Data Sharing, Data Cleansing, Data Processing, Data Visualization Software, SQL, Data Management
4.8
Rating, 4.8 out of 5 stars
114K reviews
Beginner · Course · 1 - 4 Weeks