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
Applied Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Interactive Data Visualization, Exploratory Data Analysis, Data Cleansing, Jupyter, Matplotlib, Data Analysis, Pandas (Python Package), Data Manipulation, Seaborn, Data Import/Export, Predictive Modeling, Web Scraping, Automation, Data Science, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
58K reviews
Beginner · Specialization · 3 - 6 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
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
Macquarie University
Excel Fundamentals for Data Analysis
Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Manipulation, Spreadsheet Software, Data Transformation, Data Validation, Data Analysis, Pivot Tables And Charts, Automation
4.8
Rating, 4.8 out of 5 stars
4.1K reviews
Intermediate · Course · 1 - 3 Months
Status: Free
Eindhoven University of Technology
Process Mining: Data science in Action
Skills you'll gain: Process Analysis, Process Improvement, Business Process Management, Data Mining, Business Process Modeling, Process Optimization, Data Processing, Performance Analysis, Big Data, Real Time Data, Data Science, Verification And Validation
4.7
Rating, 4.7 out of 5 stars
1.2K reviews
Intermediate · Course · 1 - 3 Months
Status: AI skills
IBM
IBM Data Analyst
Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Generative AI, SQL, 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
University of California San Diego
Big Data
Skills you'll gain: Apache Spark, Apache Hadoop, Data Integration, Exploratory Data Analysis, Big Data, Graph Theory, Data Pipelines, Database Design, Data Modeling, Regression Analysis, Data Mining, Applied Machine Learning, Data Presentation, Scalability, Data Processing, Statistical Analysis, Data Management, NoSQL, Database Management Systems, Network Analysis
4.5
Rating, 4.5 out of 5 stars
14K reviews
Beginner · Specialization · 3 - 6 Months
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
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
Multiple educators
DeepLearning.AI Data Engineering
Skills you'll gain: Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Storage Technologies, Data Architecture, Data Transformation, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Apache Hadoop, Extract, Transform, Load, Data Lakes, Amazon Web Services, Apache Spark, Database Systems, Data Integration, Infrastructure as Code (IaC), Terraform
4.8
Rating, 4.8 out of 5 stars
440 reviews
Intermediate · 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
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