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

Microsoft
Data Analysis and Visualization with Power BI
Skills you'll gain: Dashboard, Power BI, Data Storytelling, Data Visualization Software, Microsoft Power Platform, Data Presentation, Advanced Analytics, Statistical Reporting, Interactive Data Visualization, Business Intelligence, Data Analysis, Web Content Accessibility Guidelines
4.7
Rating, 4.7 out of 5 stars
725 reviews
Beginner · Course · 1 - 3 Months
Meta
Data Analysis with Spreadsheets and SQL
Skills you'll gain: Data Visualization Software, Spreadsheet Software, Correlation Analysis, Google Sheets, Dashboard, Data Analysis, Data Storytelling, Tableau Software, Descriptive Statistics, Data Cleansing, Exploratory Data Analysis, Excel Formulas, Data Manipulation, Statistical Analysis, SQL
4.6
Rating, 4.6 out of 5 stars
213 reviews
Beginner · Course · 1 - 3 Months
Duke University
Pandas for Data Science
Skills you'll gain: Pandas (Python Package), Data Cleansing, Data Manipulation, NumPy, Query Languages, Data Transformation, Data Integration, Python Programming, Data Import/Export, Data Analysis, File Management, Debugging
4.3
Rating, 4.3 out of 5 stars
8 reviews
Beginner · Course · 1 - 4 Weeks
University of Illinois Urbana-Champaign
Data Mining
Skills you'll gain: Data Visualization, Data Visualization Software, Text Mining, Data Presentation, Interactive Data Visualization, Data Storytelling, Dashboard, Visualization (Computer Graphics), Tableau Software, Data Mining, Plot (Graphics), Natural Language Processing, Unsupervised Learning, Unstructured Data, Statistical Analysis, Graphing, Analytics, Machine Learning Algorithms, Big Data, Data Analysis
4.5
Rating, 4.5 out of 5 stars
2.9K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free
Coursera Project Network
Data Science Challenge
Skills you'll gain:
4.7
Rating, 4.7 out of 5 stars
160 reviews
Intermediate · Guided Project · Less Than 2 Hours
Status: New
Microsoft
Microsoft Data Visualization
Skills you'll gain: Data Storytelling, Data Analysis Expressions (DAX), Data Presentation, Power BI, Data Ethics, Dashboard, Data Visualization Software, Data Modeling, Data Governance, Extract, Transform, Load, Data Visualization, Business Intelligence, Interactive Data Visualization, Data Analysis, Statistical Analysis, Data Architecture, Correlation Analysis, Data Cleansing, Data Transformation, Database Design
4.6
Rating, 4.6 out of 5 stars
52 reviews
Beginner · Professional Certificate · 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, Data Infrastructure, Cloud Infrastructure, Cloud Storage, Big Data, Tensorflow, Unstructured Data, Data Integration, Data Processing, Data Visualization Software, Apache Hadoop, Apache Spark
4.6
Rating, 4.6 out of 5 stars
18K reviews
Intermediate · Specialization · 3 - 6 Months
University of Illinois Urbana-Champaign
Accelerated Computer Science Fundamentals
Skills you'll gain: C++ (Programming Language), Data Structures, Object Oriented Programming (OOP), Object Oriented Design, Graph Theory, Development Environment, Data Storage, Computer Programming, Software Engineering, Algorithms, Data Storage Technologies, Debugging, Program Development, Database Systems, Database Theory, Network Routing, Computational Thinking
4.7
Rating, 4.7 out of 5 stars
3.5K reviews
Intermediate · Specialization · 1 - 3 Months
Google Cloud
Google Cloud Database Engineer
Skills you'll gain: Cloud Infrastructure, Application Deployment, Infrastructure As A Service (IaaS), Kubernetes, Database Architecture and Administration, MySQL, Identity and Access Management, Cloud Computing, Data Migration, Cloud Management, Cloud API, Oracle Databases, Databases, Cloud Storage, Network Infrastructure, Microsoft SQL Servers, Cloud Security, Cloud Applications, Google Cloud Platform, Database Administration
4.7
Rating, 4.7 out of 5 stars
49K reviews
Intermediate · Specialization · 3 - 6 Months
PwC
Data-driven Decision Making
Skills you'll gain: Analytics, Business Analytics, Data Analysis, Data-Driven Decision-Making, Business Intelligence, Big Data, Data Visualization, Data Science, Statistical Analysis, Data Visualization Software, Data Processing, Data Collection
4.6
Rating, 4.6 out of 5 stars
6.1K reviews
Beginner · Course · 1 - 4 Weeks
IBM
Introduction to Data Engineering
Skills you'll gain: Extract, Transform, Load, Data Architecture, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Storage Technologies, Apache Hadoop, Relational Databases, Apache Spark, Data Lakes, Databases, SQL, Data Mart, Data Security
4.7
Rating, 4.7 out of 5 stars
3.1K reviews
Beginner · Course · 1 - 4 Weeks
University of California San Diego
Big Data
Skills you'll gain: Apache Spark, PySpark, Apache Hadoop, Data Integration, Exploratory Data Analysis, Big Data, Statistical Reporting, Data Pipelines, Data Modeling, Regression Analysis, Data Mining, Applied Machine Learning, Scalability, Data Processing, Statistical Analysis, Databases, Data Management, NoSQL, Database Management Systems, Technical Communication
4.5
Rating, 4.5 out of 5 stars
14K reviews
Beginner · Specialization · 3 - 6 Months