Bachelor of Science in Data Science

Programs That Work for Your Future 

Turn your curiosity into career power with CU Denver's Data Science programs. 

Whether you're just starting out or ready to advance your career, CU Denver offers flexible, high-impact data science pathways designed to meet you where you are-and take you where you want to go. 

With your Bachelor of Science in Data Science you will get a strong foundation in programming, statistics, and data ethics, with hands-on experience built into every step. This degree is perfect if you want to launch into the world of data-driven discovery across industries like tech, healthcare, transportation, and more. 

CU Denver's Data Science degree is interdisciplinary by design-a collaboration between the College of Liberal Arts and Sciences, the College of Engineering, Design and Computing, and the Business School. You won't just study data—you'll learn how to use it to solve real-world problems from multiple angles. 

Why This Matters

Data science is one of the fastest-growing fields in the U.S. With employers urgently seeking skilled analysts, CU Denver gives you the tools, mentorship, and industry connections to meet your moment-and shape the future. 

A Bachelor of Science in Data Science opens the door to a wide range of exciting and impactful careers across industries.

With the ever-growing importance of data in decision-making, innovation, and automation, data science professionals are in high demand-from tech startups and Fortune 500 companies to healthcare organizations, government agencies, and financial institutions. Whether you're interested in solving real-world problems, developing cutting-edge machine learning models, or uncovering insights that drive business strategy, a data science degree equips you with the analytical, computational, and communication skills needed to thrive in today's data-driven world. 

Career trajectories

Data Analyst 

Interpret raw data and turn it into actionable insights using tools like Excel, SQL, and visualization platforms. They help organizations make informed decisions by identifying trends and patterns in data. 

Data Scientist 

Use statistical methods, machine learning, and programming to build predictive models and solve complex business problems. They often work with large datasets to forecast trends or automate decision-making processes. 

Machine Learning Engineer 

Design, build, and deploy ML models into production environments. They bridge the gap between data science and software engineering, optimizing algorithms for real-time performance and scalability. 

Business Intelligence (BI) Developer 

Create and manage business intelligence solutions, such as dashboards and reports, using tools like Power BI or Tableau. They ensure stakeholders can access key metrics to drive strategic decisions. 

Data Engineer 

Develop and maintain the architecture (e.g., databases and large-scale processing systems) that supports data collection, transformation, and storage. They ensure data pipelines are efficient, reliable, and scalable. 

Quantitative Analyst (Quant)

Apply mathematical and statistical models to financial data to guide investment strategies. They often work in finance and banking sectors and use programming and data modeling to assess risks and predict market behavior. 

AI/Deep Learning Specialist 

Focus on building advanced neural networks for tasks such as image recognition, natural language processing, or autonomous systems. They often work in research, healthcare, or tech industries pushing the boundaries of artificial intelligence. 

Healthcare Data Analyst 

Work with medical data to improve patient outcomes, hospital efficiency, and public health policies. They might analyze treatment success rates, operational costs, or disease trends. 

Bachelor of Scienct (BS) in Data Science

General: 67-68 credit hours

The explosive growth in data collection has created demand for individuals who can understand how to make decisions and predictions in the context of uncertainty through use of experimental design, statistical methods, and programming, especially in the context of large data sets. The Data Science BS provides a vigorous curriculum that will prepare students to meet this demand.  

The Data Science BS provides you with fundamental training for the field of Data Science and allows the flexibility to explore data science applications in many areas of study. 

Explore topics like:  

Mathematics and Statistics 

• Calculus I and II—Fundamental for understanding algorithms and optimization. 
• Linear Algebra—Essential for machine learning and data modeling. 
• Probability and Statistics—Core to hypothesis testing, predictive modeling, and statistical inference. 

Computer Science and Programming 

• Introduction to Programming—Often in Python, R, or Java. 
• Data Structures and Algorithms—Foundational for building efficient and scalable software. 
• Software Engineering Principles—Focused on building, testing, and maintaining codebases.  

Data Management 

• Databases and SQ—Learn how to store, query, and manage large datasets. 
• Data Wrangling and Cleaning—Techniques to prepare raw data for analysis. 

Machine Learning and Artificial Intelligence 

• Supervised and Unsupervised Learning—Regression, classification, clustering, etc. 
• Neural Networks and Deep Learning—Introductory courses on building intelligent systems. 

Data Visualization and Communication 

• Data Storytelling—Learn how to interpret and communicate findings effectively. 
• Visualization Tools—Use platforms like Tableau, Power BI, or programming libraries like Matplotlib and Seaborn. 

Ethics and Social Impacts of Data 

• Data Privacy and Security—Explore regulations and best practices. 
• Bias in Algorithms—Understand the societal impact and ethical implications of data science work. 

Capstone Project or Internship 

A senior project, portfolio, or real-world internship where students apply their skills to solve practical problems using real datasets. 

CU Denver Core: 34-40 Hours 

You’ll be educated in:

• English and Mathematics
• International and Cultural Diversity Perspectives
• Arts and Humanities
• Behavioral, Physical, and Social Sciences

 Undergraduate Graduation Requirements—15 Hours 

These courses give you a better understanding of the issues and skills you need to succeed.

Topics include:  

• Logic, Language, and Scientific Reasoning 
• Psychology 
• Writing for the Sciences 
• Public Health

Electives and/or foreign language proficiency 

You may also need to take coursework in a foreign language offered through Modern Languages. Talk to your advisor for details, especially if you’ve taken foreign language courses or have experience in a foreign language in your past. 

Double Majors

You, like many of our students, may be interested in a double major.  Common combinations include: 

Computer Science 

Why it works: Deepens technical skills in programming, algorithms, and software development. This combination is powerful for roles in machine learning engineering, AI, or tech R&D. 

Mathematics

Why it works: Strengthens theoretical foundations in probability, statistics, and modeling. Ideal for careers in quantitative finance, research, or graduate studies in analytics or applied math.

Economics 

Why it works: Equips students to analyze markets, policies, and financial systems using data. Excellent for careers in econometrics, policy analysis, consulting, or fintech.

Business Administration or Finance

Why it works: Combines data-driven decision-making with business acumen. Ideal for careers in business intelligence, financial analytics, or strategic consulting.

Psychology 

Why it works: Blends behavioral science with data analysis, supporting roles in UX research, cognitive science, and mental health analytics. Useful in human-centered AI design as well.

Biology or Public Health 

Why it works: Perfect for students interested in bioinformatics, epidemiology, or healthcare analytics. Supports careers in pharmaceuticals, hospitals, or research labs.

Political Science 

Why it works: Adds depth in policy, governance, and public opinion research. Valuable for civic tech, government analytics, and roles at think tanks or NGOs.

Environmental Science 

Why it works: Merges ecological expertise with data modeling to address climate change, sustainability, and conservation challenges using quantitative tools.

Statistics

Why it works: Refines the mathematical backbone of data science with a strong focus on inference, design of experiments, and advanced modeling techniques. 

Sociology 

Why it works: Enables analysis of social patterns, inequality, and human behavior through data. Useful for public policy, urban planning, and social impact roles. 

Once you have completed a Bachelor degree you may want to continue your education at the graduate level.

Master of Science in Data Science

This graduate program dives deep into machine learning, data visualization, and advanced computational methods-equipping you for leadership roles in fields like AI, fintech, or public health. Designed for flexibility, the MS can be completed online or in person. 

Graduate Certificate in Data Science

Fast-track your future. In just one year, you'll gain essential skills in data analysis and modeling. Ideal for working professionals, career pivoters, or anyone looking to build data fluency fast. 

Graduate Data Science learning is available also as a concentration/certificate within many of our Colleges.

Business 

The CU Denver Business School provides students with fundamental training while allowing students to focus their data science training on applications related to Business. Degrees available:

• MS Business Analytics 
• MS Information with a Business Intelligence Specialization 
• Energy and Commodity Analytics for Analysts Certificate 

Chemistry

The Graduate Certificate in Data Science and Chemistry option provides students fundamental training for the field of Data Science while allowing you to focus your data science training on applications related to Chemistry. 

Computer Science

The Data Science in Biomedicine Trac—MS in Computer Science option provides you with fundamental training for the field of Data Science where you focus your data science training on applications related to Computer Science. 

The program’s student learning goals that define what the students should know and be able to do by the time of graduation are to: 

• Math and Programming Skills: Apply the math and programming skills necessary for the work of data science. 
• Data Cycle: Explore technical and practical data science by applying the data cycle to transform data into knowledge. 
• Data Preparation: Assess and improve the quality of data relative to analytical needs. 
• Data Management: Address data challenges of volume, variety, and velocity to enable efficient and effective data analysis. 
• Data Analysis: Apply techniques, methodologies, and technologies for various forms of data analysis such as data modeling and data mining. 
• Data Visualization: Create visualizations of complex data and results for delivery to diverse audiences. 
• Data Storytelling: Explain data and results in writing and verbally, equipping stakeholders to make data-informed decisions. 
• Data Ethics: Assess ethical implications in data science, such as privacy and bias. 
• Application Domains: Apply data science in a variety of domains, such as healthcare, social sciences, natural sciences, physical science, business, education, and public administration. 
• Interprofessional Collaboration and Teamwork: Exhibit the qualities of an effective interprofessional collaborator as part of a data science team and within organizations with diverse roles.

Graduates will be able to demonstrate these capabilities in a broad range of data science activities.  The degree will prepare students for careers as data analysts, data scientists, data  strategist and many other diverse careers that rely on data, which is essentially every corner of the job market today. 

The cost of tuition for the BS in Data Science is different for in-state and out-of-state students. See the link for the current table of rates.

Residents of Western Interstate Commission for Higher Education (WICHE) states may qualify for reduced tuition rates. The Western Undergraduate Exchange (WUE) program requires students to maintain current residency in WICHE state until degree completion. 

Learn about the WUE program 

Scholarships

Each year, CU Denver undergraduate students are awarded over $30 million in scholarships from institutional, local, state, and national sources. Learn more, and apply here. 

Other opportunities

Many departments and offices at CU Denver offer student employment (including work-study, student hourly positions) through LynxConnect. Learn more here.

Admission Requirements 

If you are an incoming freshman to CU Denver (in-state, out-of-state, and international applicants), you can apply through either the Common Application or the Milo Application. Transfer students will need to submit the Milo Application.  

Incoming first-year students 

CU Denver requires that students complete the Colorado Higher Education Admission Requirements (HEAR). You will not have to meet all Minimum Academic Preparation Standards (MAPS) for admission, but you will need to complete CU Denver coursework by graduation. 

Transfer Students 

We have strong connections with other four-year and community colleges. If you have completed more than 24 credits of transferable coursework, you will be evaluated for admission on the basis of your college GPA without regard to your high school performance. If you have fewer than 24 credits, you will be evaluated based on both your high school and college GPAs. For more information and to plan your transfer, see transfer admissions in the admissions office. 

International Students 

You will need to begin your application through the Office of International Affairs. They will help you manage your application process. 

Apply to CU Denver

Spring

Domestic Application: January 1 
International Applications: Priority is September 15, and Final is October 15

Summer

Domestic Applications: May 15 
International Applications: Priority is January 15, and 
Final is March 15 

Fall

Domestic Applications: August 1
International Applications: Priority is March 15, and
 Final is May 15