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

Status: New
University of Colorado Boulder
Introduction to Bayesian Statistics for Data Science
Skills you'll gain: Bayesian Statistics, Statistical Inference, Statistical Modeling, Predictive Analytics, Statistical Methods, Data Ethics, Data Science, Probability, Regression Analysis, Analytical Skills, Probability Distribution
Intermediate · Course · 1 - 3 Months
Johns Hopkins University
The Data Scientist’s Toolbox
Skills you'll gain: Rmarkdown, Version Control, Data Science, Big Data, Git (Version Control System), GitHub, Data Analysis, R Programming, Statistical Programming, Development Environment, Integrated Development Environments, Software Installation
4.6
Rating, 4.6 out of 5 stars
34K reviews
Mixed · Course · 1 - 4 Weeks
University of California, Santa Cruz
Bayesian Statistics: From Concept to Data Analysis
Skills you'll gain: Bayesian Statistics, Statistical Inference, Data Analysis, Probability, Statistical Modeling, Statistical Analysis, Microsoft Excel, Probability Distribution, R Programming, Regression Analysis
4.6
Rating, 4.6 out of 5 stars
3.2K reviews
Intermediate · Course · 1 - 4 Weeks
Stanford University
Algorithms
Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Computational Thinking, Network Analysis, Analysis, Programming Principles, Probability & Statistics, Network Routing, Probability, Operations Research, Design Strategies
4.8
Rating, 4.8 out of 5 stars
5.9K reviews
Intermediate · Specialization · 3 - 6 Months
Johns Hopkins University
Command Line Tools for Genomic Data Science
Skills you'll gain: Unix Commands, Bioinformatics, Unix, Data Management, Command-Line Interface, Molecular Biology, Linux Commands, Big Data, File Management, Data Analysis Software, Data Processing
4
Rating, 4 out of 5 stars
560 reviews
Mixed · Course · 1 - 4 Weeks
University of Colorado Boulder
Introduction to Data Analytics for Business
Skills you'll gain: Data Governance, Analytics, Business Analytics, Data Storage, Data Management, Big Data, Databases, Business Intelligence, Data Analysis, Relational Databases, Data Quality, SQL, Organizational Structure, Cloud Computing
4.7
Rating, 4.7 out of 5 stars
3.2K reviews
Beginner · Course · 1 - 4 Weeks
Duke University
Bayesian Statistics
Skills you'll gain: Bayesian Statistics, Statistical Hypothesis Testing, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Analysis, Regression Analysis, Data Analysis, R Programming, Probability, Data-Driven Decision-Making, Probability Distribution
3.8
Rating, 3.8 out of 5 stars
797 reviews
Intermediate · Course · 1 - 3 Months
University of Michigan
Python Data Structures
Skills you'll gain: Data Structures, Python Programming, Programming Principles, Data Import/Export, Data Manipulation, Development Environment, File Management
4.9
Rating, 4.9 out of 5 stars
97K reviews
Beginner · Course · 1 - 3 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
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
University of Michigan
Programming for Everybody (Getting Started with Python)
Skills you'll gain: Programming Principles, Computer Programming, Python Programming, Software Installation, Development Environment
4.8
Rating, 4.8 out of 5 stars
231K reviews
Beginner · Course · 1 - 3 Months
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