Online data science degree

Start your online data science degree

With a Bachelor of Science in Data Science degree, you’ll gain the fundamental knowledge needed to analyze, manipulate and process data sets using statistical software. Learn extract, transform and load (ETL) processes for integrating data sets for business intelligence platforms. Discover techniques to transform structured and unstructured data sets into meaningful information to identify patterns and drive strategic decision making.

Our online data science degree can help you develop career-relevant skills in data mining, data modeling, machine learning, programming languages and statistical analysis. The practical application of these skills in your courses will help you prepare for a variety of employment opportunities in data science and business or IT management.

Gain career-relevant programming and machine learning skills
Learn data mining, modeling, storytelling and visualization techniques
Customize your program at any time through your first year by adding a certificate

Transfer credits

Save time and money on your bachelor's degree with eligible transfer credits.

Ways to save

Your work, life, and school experiences may give you a head start on your degree.

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Courses

Browse courses for your online data science degree

Education should hold practical value. That’s why our data science program is built with input from industry leaders. Our courses, activities and assignments map to career-relevant skills that prepare students for diverse data science roles, such as data analysts or database architects.

Look for this icon to see which skills you’ll learn in a course.

Core Courses

3 Credits

This course introduces practices in data analytics foundational to the industry and the field of data analytics. Covered are theories of analytics, the phases of the analytics lifecycle, analysis and exploration of data, relevant statistics for data modeling, data visualization, and the tools used for data analytics.

3 Credits

This course provides an overview of advanced spreadsheet functions used in data analysis. Topics include filters, sorts, lookups, formulas, functions, macros, pivot tables, graphs and charts, dashboards, forms, reports, queries, statistical analyses, and data validation.

3 Credits

This course provides a foundational workshop on data structures, which is a functional component of business intelligence (BI) within an organization. Building upon basic programming and database structure, this course builds competencies for the student to recognize the structure of data contained in deployed enterprise information systems.

3 Credits

This course provides an introduction to the Python programming language. Students will review the function and use of variables, data types, lists, tuples, functions, classes, files, exceptions, search/sort algorithms, memory management, and code testing. Additional topics may include Integrated Development Environments (IDEs), data visualization, global data sets, and Web Application Programming Interfaces (APIs).

3 Credits

This course covers fundamental database concepts including SQL, non-relational databases, distributed databases and database architectures. Students are provided an overview for how to manage, display, sort, group, retrieve, and organize data for the application or tool associated with the software development taking place within an organization

3 Credits

This course provides an overview of R, which is a programming language commonly used for data science, statistical analysis, and data visualization. Topics include syntax, variables, operators, functions, data structures, statistical data sets, and graphical presentation.

3 Credits

This course provides an overview of applied business research, statistical tools, and data analytics used to support strategic decision making. Students will examine methods used to frame business problems, conduct research, collect and evaluate data for validity and reliability, determine patterns and trends in performance, and effectively present conclusions.

3 Credits

Structured Query Language (SQL) is a domain-specific language used to store, query, and manipulate data within databases. This course provides an overview of SQL and relational database applications with a focus on SQL syntax, data types, keywords, functions, structured and unstructured data, and data modeling.

3 Credits

This course provides an overview of database administration, including database implementation, configuration, authentication, monitoring, backup, and security. Students will examine database architecture with a focus on business requirements, data integrity, and the ethical handling of private data.

3 Credits

This course provides an overview of Exploratory Data Analysis (EDA), including the cleaning, preparation, exploration, and visualization of data. Students will review machine learning algorithms, neural networks, and Artificial Intelligence (AI) concepts used to analyze data sets and build intelligent applications.

3 Credits

This course will introduce students to data analytics and modeling through contemporary business tools. Students will examine how data is architected and organized. After completion of this course, students will be able to understand the different data models used to store data, several schemas that drive how data is structured, and provide other database concepts relating to the design and architecture of data.

3 Credits

This course covers data mining techniques for structured and unstructured data. Learn programming techniques and algorithms to transform large quantities of data into usable Business Intelligence (BI).

3 Credits

This course introduces students to tools and techniques needed to present data, both simple and complex, to gain support and recommend business decisions. Student will use graphical tools such as graphs, animation, and presentation techniques to communicate the message behind the data and improve decision making. Topics include requirement gathering, graphical representation of data sets, visualization techniques and tools, and data validation.

3 Credits

This course reviews the origin and applications of big data within the framework of current businesses. Topics include data validation, processing, and predictive analytics used in a timely manner to make informed decisions.

3 Credits

This course provides an overview of machine learning, including the use of algorithms, neural networks, and supervised, unsupervised, and reinforcement learning to automate advanced computer tasks.

3 Credits

This course provides an overview of predictive modeling techniques, with a focus on statistical analyses, data mining, and machine learning tools used to find patterns and trends, identify potential risks, and forecast probable outcomes within various data sets.

3 Credits

This capstone course combines the skills and applies the knowledge from various courses in the Bachelors of Science in Data Science program. Student teams working with large data sets combine the concepts of statistics, programming, data mining, data analysis, and data visualization to design, implement, and present a data science project representing a real-world application to decision-making executives.

General Education Courses

3 Credits

This course transitions students through the foundations of study at University of Phoenix. Students develop personal strategies for achieving educational goals and develop skills in critical thinking, collaboration, and communication.

3 Credits

This course provides an overview of the key components of comprehensive wellness. Based on a preventive model, the course will allow learners to explore choices that promote wellness with goals of living longer and better.

3 Credits

The course introduces theories and concepts in psychology that will foster academic success and provide students with opportunities to synthesize and apply that knowledge.

3 Credits

This course develops the reading, writing, and critical thinking skills that are essential for academic and life success.

3 Credits

Students learn how to think critically, focusing on developing the necessary tools and skills to analyze problems, make decisions, and formulate well-supported points of view on key academic, social, and professional issues.

3 Credits

This course extends practice in critical reading, writing, and thinking. Emphasis is given to developing an effective writing process that takes into account audience and rhetorical purpose.

3 Credits

This course provides an applied approach to team building, collaboration, and conflict resolution. Students must understand and apply these concepts within academic and professional settings. Students develop structures, processes, and strategies to create and maintain effective teams. Gender, cultural, and individual considerations in team dynamics are also explored.

3 Credits

The course provides an introduction to the most prominent forms of media that influence and impact social, business, political, and popular culture in contemporary America. It explores the unique aspects of each medium as well as interactions across various media that combine to create rich environments for information sharing, entertainment, business, and social interaction in the United States and around the world.

3 Credits

This course introduces students to thinking about and working with numbers by examining the day-to-day and societal importance of money.

3 Credits

This in-depth environmental science course examines how people use science to understand how they relate to the environment. The course explores relationships between people and ecosystems, and the science behind how ecosystems work. It reviews the historical development of the environmental movement, interactions between humans and natural ecosystems, and more specifically, the role of a growing population and associated pressures on natural resources. This course further examines how economics, natural systems, and conservation are interrelated. The many forms of pollution as well as types of energy resources are addressed. This course challenges students to consider the impact of lifestyle choices on environmental sustainability.

3 Credits

Students apply advanced quantitative reasoning skills to solve real-world problems. This course emphasizes modeling skills, statistical methods, and probability to create, analyze, and communicate solutions.

3 Credits

This applications-driven course prepares students to critically analyze and solve problems using quantitative reasoning. Students approach real-world scenarios using numerous reasoning skills and mathematical literacy to draw conclusions.

Electives

3 Credits

This course provides an overview of business analysis with an in-depth examination of planning and monitoring, elicitation and collaboration, and requirements life cycle management. Students will examine key aspects of planning, stakeholder engagement, governance, information management, performance improvement, elicitation, communication, collaboration, prioritization, and assessment related to business analysis.

3 Credits

This course examines the use of business intelligence in value-driven decision making. Topics include data preparation, modeling, visualization, and analysis, as well as the deployment and management of datasets, workspaces, and other deliverables for business analysis and forecasting needs.

3 Credits

This course addresses the main standards for data integration, movement or replication and federation. Students will investigate transparency and emulation, cleaning, archiving, and information preservation across systems.

3 Credits

This course is a study in Java programming. It covers topics around Java programming, variables, expressions, using branches and loops, storing data in arrays and using methods.

3 Credits

This course will provide the knowledge and skills required to understand foundational and advanced cloud terminologies/methodologies; to implement, maintain, and deliver cloud technologies and infrastructures (e.g., server, network, storage, and virtualization technologies); and to understand aspects of IT security and use of industry best practices related to cloud implementations.

3 Credits

This course explores the recent technological advances associated with digitized data flows, which have recently opened up new horizons for AI. Students will gain insight into some of the areas of application of Big Data in AI, including robotics, home automation, health, security, image recognition and natural language processing.

3 Credits

This course examines traditions and developments in the visual and performing arts including music, dance, theater, cinema, visual arts, and architecture. Students will be introduced to the elements of each genre, along with an overview of its historical development in Western European tradition.

3 Credits

This course covers the skills necessary for effective written and oral communication in the work environment and in modern society. The course reviews basic communication theories and discusses the fundamentals of interpersonal, written, and oral communication skills. This course emphasizes applying these theories and skills to group processes and professional situations.

3 Credits

This course introduces the basic concepts of human nutrition to highlight ways that students can integrate healthy nutrition into their lifestyles. Principles of digestion and absorption, the function of nutrients, lifecycle nutrition practices, disease prevention, diet modifications, and weight management are covered. Practical application of these principles to the students' lives is emphasized.

Online data science degree requirements

You’ll need 120 credits (3 credits per course) to complete this online Bachelor of Science in Data Science degree. Your course schedule may vary based on transferable credits or credits earned through the University's Prior Learning Assessment.

You’ll learn about programming, database administration, exploratory data analysis and predictive modeling. Perform statistical analyses, analyze various types of data sets, evaluate business decisions with data mining and modeling, and communicate business strategies via data visualization and storytelling. Applying what you learn to real-world business scenarios will provide you with skills and knowledge applicable to your career.

Here’s where you’ll pick up the bulk of your program-specific knowledge. You’ll learn about key data science topics, such as advanced spreadsheet applications, programming in Python, R, structured query language (SQL), database administration, big data and more.

Here’s where you’ll explore a variety of topics that may interest you. Electives are an excellent way to customize your degree to best fit your career aspirations. You can also add a certificate and build out your expertise in a specialty area like cybersecurity or cloud computing.

Here’s where you’ll study different disciplines to lay the foundation for your online data science degree. You may learn soft skills like communication, critical thinking, decision making, problem solving and storytelling that will be further built upon in your core courses.

Plan your schedule

Your academic counselor will help schedule your courses for a Bachelor of Science in Data Science degree.

As a student pursuing the Bachelor of Science in Data Science degree, you can transition into a Master of Business Administration (MBA), Master of Management (MM), Master of Information Systems or a Master of Science in Data Science. You may complete up to three courses (or a direct equivalency) as part of your electives while finishing your bachelor’s degree.

Customize your online data science degree

Tailor your bachelor’s in data science program to your interests by selecting a certificate to add within the credit requirements. At any time through your first year, you can choose to pursue any of our undergraduate business certificates or information technology certificates alongside your bachelor’s degree. Graduating with a certificate can allow you to specialize in a specific area or supplement your data science knowledge.

Certificate options you might consider for your data science degree include:

Learn about cost of attendance

Earn career-relevant skills in weeks – not years.

Learning shouldn’t take years to put into practice. That’s why we’re empowering you to build career-relevant skills with every five- to six-week course.

We’ve worked with the labor market researcher Lightcast to identify in-demand skills for occupations and mapped those to our related associate, bachelor’s and master’s degree programs.

Learn about skills

Tuition

Paying for school

Tuition is based on number of credit hours per course. Courses are typically 3 credits, but can range from 1-6 credits. Costs do not include savings opportunities like transfer credits and scholarships.

Undergrad cost per course

$1,364 / course

Cost per credit

Credits per course

Resource fee

$398

+ $170

Estimated cost per course

$1,364

An illustration showing a couple pushing a stroller with a dollar sign and clock in the background

What affects the overall cost of my program?

Your full program cost can vary by:

Savings opportunities. Your cost could be reduced with eligible transfer credits, scholarships, employer discounts and more. Students with eligible credits and relevant experience on average saved $11K and 1 year off their undergraduate degree at University of Phoenix.

With our Tuition Guarantee, you pay one flat, affordable rate from the moment you enroll to the day you graduate from your program.

Discover ways to save time and money on your degree with our Savings Explorer^® tool:

Go to Savings Explorer®

Explore scholarships

Learn about cost of attendance

Transfer credits

Your prior eligible college credits can save you time and money, helping you graduate faster. That’s why we’ve accepted transcripts from 5,000+ institutions. Check to see if you can apply eligible transfer credits from an institutionally accredited university or college toward your data science degree.

Learn about transfer credits

Save time and money when you transfer eligible credits toward your bachelor's in data science.

Learn about Cost of Attendance (COA)

University of Phoenix bachelor's in data science vs other universities

	Phoenix	ASU Online (BAB)	Capella	DeVry	GCU	Purdue Global	SNHU	Strayer
Tuition rate Tuition rate	Tuition rate $398	Tuition rate $574	Tuition rate $365 per 1000-2000 level credit $415 per 3000-4000 level credit	Tuition rate $514	Tuition rate $485	Tuition rate $371	Tuition rate $330	Tuition rate $338.89
Typical credits per course Typical credits per course	Typical credits per course 3	Typical credits per course 4	Typical credits per course 6	Typical credits per course 4	Typical credits per course 4	Typical credits per course 6	Typical credits per course 3	Typical credits per course 4.5
Resource fee Resource fee	Resource fee $170	Resource fee $645*	Resource fee $600*	Resource fee $550*	Resource fee $702*	Resource fee $1,056*	Resource fee $0*	Resource fee $75*
Estimated cost per course Estimated cost per course	Estimated cost per course $1,364	Estimated cost per course $2,941	Estimated cost per course $3,090	Estimated cost per course $2,606	Estimated cost per course $2,642	Estimated cost per course $3,282	Estimated cost per course $990	Estimated cost per course $1,600
Total program length Total program length	Total program length 120 cr.	Total program length 120	Total program length 180	Total program length 124	Total program length 120	Total program length 180	Total program length 120	Total program length 180
Length of course Length of course	Length of course 5 wks	Length of course 7.5 weeks	Length of course 10 weeks	Length of course 8 weeks	Length of course 7-8 weeks	Length of course 10 weeks	Length of course 8 weeks	Length of course 11 weeks
Tuition guarantee promise Tuition guarantee promise	Tuition guarantee promise Yes	Tuition guarantee promise No	Tuition guarantee promise No	Tuition guarantee promise No	Tuition guarantee promise NO	Tuition guarantee promise No	Tuition guarantee promise No	Tuition guarantee promise No

Data pulled on September 27, 2024

[1] $365 per 1000-2000 level credit; $415 per 3000-4000 level credit

Source of data: For each institution, the data are publicly available in multiple locations, including Academic Catalogs, Program pages, Tuition and fees pages, and syllabi. All data are publicly available on the websites.

Certain licensure programs and coursework in other degree programs may have additional fees. Please check with your advisor or course catalog for additional info.

Tuition is based on number of credit hours per course. Courses are typically 3 credits, but can range from 1-6 credits.

The Savings Explorer tool can help you find ways to save on your education

Try our Savings Explorer® tool

Eligible students saved:

$11,000 & 1 year

Students with eligible credits and relevant experience on average saved $11k and 1 year off their undergraduate degree with University of Phoenix.

Explore ways to save

Try our Savings Explorer™ tool

Eligible students saved:

$11,000 & 1 year

Students with eligible credits and relevant experience on average saved $11k and 1 year off their undergraduate degree with University of Phoenix.

Explore ways to save

Financial aid

You may have options when it comes to paying for college tuition and expenses, such as federal grants and loans. Our finance advisors can answer your questions about financial aid and can help guide you through the process.

Learn about financial aid

Federal Student Loan Basics

Careers & Outcomes

What can you do with a Bachelor of Science in Data Science degree?

Our online data science degree strives to meet the growing demand for data science professionals who possess a combination of IT and business skills at various organizational levels and within multiple industries. You’ll learn how to apply your skills to real-world, on-the-job tasks like creating dashboards, conducting data analyses and completing web scraping exercises – all of which will help prepare you for your future career path.

When you earn your online Bachelor of Science in Data Science degree, you’ll be equipped with a concrete set of skills you can apply on the job. You’ll learn how to:

Perform statistical analyses using data-oriented programming languages and business software.
Analyze structured and unstructured data sets for meaningful information.
Evaluate business decisions using data mining and modeling.
Communicate business strategies via data visualization and storytelling.

Business man at working on a laptop in a park

Top skills learned in this program:

Data Analytics
Data Management
Data Visualization
Business Intelligence

Learn more about skills

A bachelor’s in data science can prepare you for:

Information Systems (IS) Manager
Data Analyst
Business Intelligence Analyst
Database Architect
Research Scientist

Learn more about careers

17% growth

According to the Bureau of Labor Statistics, job growth for computer and information systems managers is projected to be much faster than average between 2023 and 2033.

The BLS Projected Growth for 2023-2033 is published by the US Bureau of Labor Statistics. This data reflects the BLS’ projections of national (not local) conditions. These data points are not specific to University of Phoenix students or graduates.

Data science industry spotlight

Data science is a field that spans various industries, such as information technology, health care, finance, manufacturing, transportation, hospitality and human resources. As a bachelor’s in data science student, you’ll learn key concepts, principles and techniques designed to prepare you to analyze data for several business applications.

48,000+

The number of openings for computer and information systems managers projected each year, on average, over the decade.

Source: U.S. Bureau of Labor Statistics | Computer and Information Systems Managers | Sep. 2022

$127,180—$207,850^[1]

The 25th to 75th percentile wage range estimate for computer and information systems managers in May 2022.

Source: U.S. Bureau of Labor Statistics | Occupational Employment and Wage Statistics | May 2022

[1] The salary ranges are not specific to students or graduates of University of Phoenix. Actual outcomes vary based on multiple factors, including prior work experience, geographic location, and other factors specific to the individual. University of Phoenix does not guarantee employment, salary level or career advancement. BLS data is not geographically based.

Admissions

Apply for free – no application fee, no obligation.

Starting your online data science degree is a big decision — and we want you to feel great about it. That’s why we remove obstacles from your application.

No SAT/ACT required
No essay required
We’ll request transcripts at no cost to you, when possible, and we accept eligible credits from over 5,000 accredited institutions.

Explore admission requirements

How to enroll at the University of Phoenix

How to enroll at University of Phoenix

Receive 1-on-1 support

You have a support team of real people you can lean on. And our academic counselors, who are with you every step of the way, have earned a 5-star rating from 90% of our surveyed students.^[1]Start a conversation with an enrollment representative today.

[1] Transactional Survey, August 2021-22 (18,645 respondents)

Call or chat with us 7 days a week.

Gabriel G., Enrollment Rep

Receive 1-on-1 support

You have a support team of real people you can lean on. And our academic counselors, who are with you every step of the way, have earned a 5-star rating from 85% of our surveyed students.^[1]

[1] Transactional Survey, September 2022-August 2023 (23,739 respondents)

Start a conversation with an enrollment representative today.

Call us at 844-937-8679 or chat with us 7 days a week.

Learn about our flexibility

Data Science Student Experience

Balance it all: work, family and school

Focus on just one 5-week course at a time, while still completing your data science degree on time. Plus, enjoy the freedom to learn when you want with a 24/7 online classroom.

Online learning resources for you

Your bachelor’s in data science includes online learning resources like test prep. You’ll also participate in data science and programming labs to demonstrate your data mining and modeling skills.

Read about online classes

Around-the-clock support and resourcess

You have a support team available up to 14 hours a day, 5 days a week.

See student resources

Phoenix provides support and resources for busy students

Faculty Spotlight

Learn from professionals working in IT

As a university built for working adults, we believe you should be taught by faculty who practice what they teach. The IT curriculum they teach today is designed to help you make an impact in your day-to-day work tomorrow, bridging the gap between academics and industry knowledge.

Daniel D'Urso, MBA, MS Computer Science

Faculty, College of Business and Information Technology

Accreditation

Accredited for 45+ years

Since 1978, University of Phoenix has maintained institutional accreditation by the Higher Learning Commission (HLC), hlcommission.org. Learn more about the value of University of Phoenix accreditation and how it benefits our students.