online bachelor's degree of data science
Spring term classes start March.
100% online learning.
Earn your degree on your schedule
$459 per credit hour.
$250 military preferred cost per credit
127 total credit hours.
earn a data science degree that can make you valuable to any business.
With this valuable degree, you’ll build a data science portfolio based on the work you complete throughout the program. When you bring this to future employers, they’ll see the depth and breadth of your experience analyzing data to solve problems. As a data science major, your portfolio will show you are prepared with the latest skills and know-how to benefit their businesses.
Gain experience in high-demand data wrangling skills.
With a data science degree, you’ll gain experience in:
- Business analytics
- Computer science
- Statistics
- Gathering and analyzing valuable data
What can you do with a data science degree?
Employers around the world are inundated with massive amounts of data. They need skilled employees to glean insights from that data for better decision-making and strategic business moves. They are seeking qualified people with the right expertise to guide them.
Throughout the data science program, you’ll be able to apply what you’re learning right away:
- Apply the data science process to formulate questions about data and solve problems.
- Transform, clean and prepare datasets for analysis.
- Recommend analysis techniques to validate hypotheses.
- Communicate a story about data to various audiences with visualizations and presentations.
- Identify ethical considerations in dataset preparation and modeling.
what you'll learn.
In this program, you’ll learn to turn complex data into meaningful insights using advanced tools, programming, and analytics techniques to solve real-world problems.
upon graduation, students will be able to:
- Problem solving and data wrangling using Python.
- Data visualization with exposure to R, Tableau and PowerBI.
- Data storytelling to be confident in front of executive leadership or any stakeholder group.
- Data analysis using statistical models, machine learning, and predictive analytics.
- Data management techniques using Python, SQL and other tools.
- Big Data storage and efficient processing with Hadoop, Spark, Data Warehousing and Deep Learning
- Creating robust analytic solutions that transform data into actionable insights.
Awards
Bellevue Stories
Data Science degree courses
Current students please login to BRUIN and select “Academic Progress” for your curriculum requirements.
Requirements (36 Credit Hours)
This course is an introduction to the field of data science and the skills required to be a data scientist. The course explores the basics of data science including: vocabulary, common programming languages, data visualization, presentations, data analysis, the history of information, data ethics, and the data science process. Students should have a better understanding of how they generate data and how data science impacts them as a consumer of this information. Prior programming experience is not needed for this course.
This course introduces the architecture, hardware, and software utilized for data science projects. Fundamental terminology, definitions, and data architecture concepts will be covered. Students will explore case studies and examples to understand the opportunities and challenges that architectural decisions impose on data science.
This course provides the theoretical basis and problem-solving experience needed to apply the techniques of descriptive and inferential statistics, to analyze quantitative data, and to improve decision making over a wide range of areas. Topics covered include descriptive statistics, linear regression, data gathering methodologies and probability, as well as confidence intervals and hypothesis testing for one and two samples. Use of technology in solving and interpreting statistical problems is emphasized. Prerequisite: MA 101 or placement via ALEKS Placement Assessment
This course provides an introduction to problem solving and computer programming using the language Python. Students will analyze problems, design and implement solutions and assess the results. Topics include fundamental programming constructs such as variables, expressions, functions, control structures and lists. Emphasis is placed on numerical and data analysis for informed decision making. Prerequisite: None
This course prepares students for the methodologies and processes required to execute a data science project. Students will learn about the critical skills required for initiating and delivering a data science project with business value: research, project management, problem solving, decision making, requirements gathering, and data analysis. This course also prepares students for making a project operational and focuses on tasks required to deploy and automate projects.
In this course, students will use various techniques and tools to explore, visualize, and present data. Students will be exposed to R, Tableau, and PowerBI to perform initial analysis and view data. Students will use statistics and programming to ask and answer insightful questions regarding data, while also learning basic storytelling and presentation concepts. Students will learn innovative ways to communicate with different levels of leadership and stakeholders.
In order to fully analyze data, mathematical concepts need to be applied to data. This course focuses on the common statistics, algorithms, and models required for data mining and predictive analytics. Some of these concepts will include: Bayesian statistics, Bayesian models, calculus concepts to understand probability distributions, and basic linear algebra. Students will learn how to problem solve and identify the right methods to apply during their analyses. Prerequisite: MA 215 Applied Statistics
It is estimated that data scientists spend about 80% of their time finding and cleaning data. The data currently being produced is infinitely variable in its structure, presentation, and scale. This course prepares students for dealing with this infinite variety of data and how to interact with disparate sources of data. Students will be exposed to data structures and data management via Python, SQL, and other tools teaching them how to acquire, prepare, clean, and automate dataset creation. Prerequisite: CIS 245 Intro to Programming.
Comments, chats, logs, etc., are rich with customer feedback and insights that if analyzed can drive business decisions and potentially reduce costs. The challenge is generating meaning and context when the data quality and type varies. This course focuses on text processing and interacting with unstructured data. Techniques for mining unstructured data such as text pre-processing, tokenization, corpus preparation, machine learning algorithms, N-gram language model, word and document vectors, and text classification will be covered in this course. Prerequisite: CIS 245 Intro to Programming.
In this course, students will apply the concepts previously learned about statistics, algorithms, and models to interact with data for the purpose of predictive analytics. Predictive analytics has the capability to help organizations identify potential impacts to their business and to support business decisions. Concepts that will be covered include: bias/variance trade-off, over-fitting and model tuning, regression models – linear, nonlinear (SVMs, K-nearest neighbors), regression trees, classification models – logistic regression, random forest, dealing with unbalanced data, feature selection, and predictor importance. Prerequisite: DSC 350
In the final course of the Data Science program students have the opportunity to demonstrate their understanding of data science by completing a term project that takes them from idea/hypothesis to presentation. Students will gather data, prepare, clean, analyze, and present their analysis and recommendation. Students will finalize their data science portfolio based on work completed throughout the program. Students will also collaborate with each other to prepare for interviews. Prerequisite: Successful completion of all other required DSC courses.
Choose one of the following courses:
With the cost of data storage consistently decreasing, data volumes are increasing and organizations are no longer forced to only store the bare minimum data. This course examines the technology required to analyze and process Big Data. Topics include: Hadoop/MapReduce, Spark/RDD, Spark/Storm Streaming, TensorFlow, Keras/Deep Learning, Kubernetes, and Docker. Prerequisite: DSC 360 Data Mining. Recommend: DSC 350 Data Wrangling for Data Science.
Generative Artificial Intelligence (GAI) is arguably one of the most transformative developments in information technology history. With uses of GAI ranging from creating essays to generating entire videos, this technology affects every industry, directly or indirectly. This course prepares students for a life of GAI by giving a thorough introduction to the evolution leading to GAI, delving into how large language models (LLMs) can work with text, and how images can be created and manipulated using GAI. Students will also explore prompt engineering and retrieval augmented generation, which is how GAI is used and grounded in truth. Prerequisites: DSC 360 Data Mining: Text Analytics & Unstructured Data (Required), DSC 400 Big Data, Technology and Algorithms (Recommended)
The major focus of this course will be the relational, dimensional and NoSQL models. Topics include relational and dimensional modeling, business intelligence, NoSQL databases and their application, SQL, application development using databases and emerging trends. Students will prepare a small application using a commercial database management system.
Kirkpatrick Signature Series Requirements (9 credit hours)
In addition to the Major Requirements, all Bellevue University students must complete the Kirkpatrick Signature Series.
This course focuses on the political and philosophical traditions of the American republic, especially as embedded in the ideals, values, traditions, founding documents, and institutions of the United States , and considers how these traditions relate to individual citizenship and global society. Prerequisite: 60 Credit Hours
This course focuses on the creative tensions that exist between the forces of tradition and change as the country undergoes social, cultural, and political change. It considers the manner in which change can renew the vitality of a republic. Prerequisite: 60 Credit Hours
This course examines civic engagement in relation to individual freedoms and responsibilities. It fosters engaged citizens, empowered to effect positive change. Prerequisite: 60 Credit Hours
Integrative General Education Credits
Major Requirements Credits
Elective Credits
= 127 total credits*
General Education Courses
Take general education courses that do more than fill a requirement. At Bellevue University, these courses build foundational skills that apply to any career—critical thinking, qualitative reasoning, and ethical leadership. And, you can take courses individually or in course clusters, which connect three courses around one theme, building skills as you go.
About general education requirements >Elective Courses
Our broad selection of electives allows you to select courses related to your major or expand your perspective in other areas of interest.
University Accreditation
Bellevue University is accredited by the Higher Learning Commission ( hlcommission.org ), a regional accreditation agency recognized by the U.S. Department of Education.
Whether a college, university, or program is accredited is important to students receiving financial aid, employers who provide tuition assistance, donors, and the federal government.
This program is considered a non-licensure degree/certificate program and is not intended for those seeking licensure or the practice of licensed profession. This program may be relevant to multiple occupations that do not require licensure and was not designed to meet educational requirements for any specific professional license or certification.
*Consult with an admissions counselor to determine your eligible credits, as well as to verify minimum graduation requirements for this degree. Transfer credits must be from a regionally accredited college or university. Bellevue University makes no promises to prospective students regarding the acceptance of credit awarded by examination, credit for prior learning, or credit for transfer until an evaluation has been conducted.
learn on your own time, from anywhere.
Flexible schedule.
Study on your own time with courses designed to fit your busy life—whether you're working, raising a family, or serving in the military.
Reliable technical support.
Access 24/7 tech support to keep you connected and focused on learning, no matter where you are.
Dedicated online student support.
From coursework access and connectivity issues to tutoring and resume assistance, we've got you covered.
Engaging online learning.
Enjoy interactive courses designed for real-world application, with multimedia content, discussions, and hands-on projects.
grow with faculty who’ve been where you are.