Best Bachelor's Data Science Degree Programs in Colorado
University of Colorado Boulder — Boulder, CO
Key Distinction: Accelerated Bachelor's-Master's degree pathway (BAM-STAT program). Graduate coursework taken as undergraduate (typically junior/senior years)
Hakia Insight: CU Boulder's BAM-STAT program lets undergraduates compress a master's degree into their junior and senior years—a rare advantage that could save $50K+ in tuition while accelerating entry to roles typically requiring a graduate degree.
CU Boulder's Bachelor's degree in Statistics & Data Science is part of an innovative BAM-STAT (Bachelor's-Accelerated Master's) program that allows currently enrolled undergraduates to earn both a bachelor's and master's degree in a shorter timeframe. Students begin taking graduate coursework as undergraduates, typically in their junior or senior years, with up to six credits double-counting toward both degrees. The program emphasizes advanced statistics and data science knowledge valued across industry applications in applied mathematics, engineering, and related fields. Graduates are prepared to contribute to data science teams and collaborate across disciplines. The Department of Applied Mathematics is consistently ranked in the top 15 programs nationally by U.S. News & World Report. The program leverages faculty mentorship and industry advisory board partnerships for networking and collaboration opportunities.
Programs Offered
- Bachelor's Degree in Statistics & Data Science — 4 years, on-campus. BS
Research Labs and Institutes
- Institute of Cognitive Science
- Cooperative Institute for Research in Environmental Sciences
- BioFrontiers Institute
Industry Partners
- Google (corporate)
- IBM (corporate)
- NIST (government)
- NOAA (government)
Notable Faculty
- Claire Monteleoni — Machine learning and climate informatics
- Jordan Boyd-Graber — Natural language processing
Admissions
GPA Requirement: 2.75 minimum (3.2+ recommended). Application Deadline: See Graduate School Admissions Deadlines.
Requirements: Complete bachelor's degree requirements, Up to six credits may double-count for both bachelor's and master's degrees
Location Advantages: Access to Denver tech corridorBoulder startup ecosystemProximity to federal research labs
Colorado Technical University-Colorado Springs — Colorado Springs, CO
Key Distinction: Capstone project requirement. Industry-standard software training
Hakia Insight: Colorado Technical's capstone requirement paired with industry-standard software training creates a portfolio-ready credential by graduation, but the school's tight focus on Intel partnerships means limited exposure to the broader tech ecosystem.
Colorado Technical University-Colorado Springs offers a Bachelor of Science in Data Science designed to prepare students for the growing field of data analytics and business intelligence. The program combines foundational computer science concepts with statistics, mathematics, and business applications. Students complete core coursework in programming languages like Python and R, database management, statistical analysis, and machine learning. The curriculum emphasizes hands-on learning through laboratory work and real-world projects. Upper-level courses focus on data visualization, predictive modeling, and big data technologies. Students are required to complete a capstone project that demonstrates their ability to solve complex data problems using industry-standard tools and methodologies. The program is designed to be flexible for working professionals, with evening and weekend class options available. Career preparation includes industry networking opportunities and partnerships with local technology companies in the Colorado Springs area.
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus. BS
Career Outcomes
Top Employers: Intel.
Location Advantages: Proximity to Colorado Springs aerospace and defense contractorsAccess to growing Colorado tech corridor
Colorado School of Mines — Golden, CO
Key Distinction: Industry-sponsored senior capstone projects. Cooperative education program
Hakia Insight: Mines' cooperative education program and industry-sponsored capstones aren't unusual, but the school's direct pipeline to energy sector employers (ExxonMobil, Chevron, Schlumberger) offers salaries and stability that tech-focused peers often can't match—a strategic advantage if you're willing to work outside Silicon Valley.
Colorado School of Mines offers a Bachelor of Science in Data Science that combines rigorous mathematical foundations with practical computational skills and domain expertise in engineering and applied sciences. The curriculum integrates core coursework in statistics, computer science, and mathematics with specialized applications in mining, petroleum, environmental, and other engineering disciplines. Students complete a capstone senior design project working on real-world data science problems often sponsored by industry partners. The program emphasizes hands-on learning through internships and cooperative education opportunities with energy, technology, and engineering companies. Students can pursue minors in various engineering disciplines or business. Undergraduate research opportunities are abundant, allowing students to work alongside faculty on cutting-edge projects in areas like geophysics, environmental modeling, and energy systems. The program's unique strength lies in its focus on applying data science to natural resources, energy, and earth systems, preparing graduates for specialized roles in these high-demand sectors while maintaining broad applicability across industries.
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus. BS
Research Labs and Institutes
- Center for Wave Phenomena
- Payne Institute for Public Policy
Industry Partners
- ExxonMobil (corporate)
- Chevron (corporate)
- Schlumberger (corporate)
- ConocoPhillips (corporate)
Career Outcomes
Median Salary: $NaN. Top Employers: IBM, Microsoft, Amazon, Intel.
Accreditations and Certifications
- Higher Learning Commission accredited
- ABET accredited
Location Advantages: Proximity to Denver tech corridorAccess to National Renewable Energy LaboratoryStrong connections to Colorado energy industry
United States Air Force Academy — USAF Academy, CO
Key Distinction: Mandatory military service commitment. Leadership training integrated throughout
Hakia Insight: The Air Force Academy's data science degree comes with a mandatory service commitment that eliminates career flexibility, but graduates gain immediate clearance and access to classified intelligence work—a rare pathway unavailable anywhere else.
The United States Air Force Academy's Data Science program is integrated within the Mathematical Sciences Department, offering cadets a rigorous analytical foundation combined with military leadership training. The curriculum emphasizes statistical modeling, machine learning, operations research, and computational methods applied to Air Force and Space Force challenges. Core coursework includes calculus, linear algebra, probability, statistical inference, programming, and database management. Advanced electives cover artificial intelligence, cybersecurity analytics, and optimization. All cadets complete a capstone research project, often addressing real Air Force operational problems. The program integrates military training, leadership development, and academic study over four years. Cadets participate in summer military training, leadership positions within the cadet wing, and may pursue research with faculty on defense-related analytics projects. Graduates commission as second lieutenants with strong quantitative skills for intelligence, operations research, acquisition, and space operations career fields. The Academy's unique military environment provides hands-on leadership experience and exposure to cutting-edge defense technologies.
Programs Offered
- Bachelor of Science in Mathematical Sciences with Data Science Focus — 4 years, on-campus. BS
Industry Partners
- Department of Defense (government)
- Air Force Research Laboratory (government)
Career Outcomes
Median Salary: $NaN. Top Employers: Intel.
Accreditations and Certifications
- Higher Learning Commission accredited
- ABET accredited
Location Advantages: Direct connection to military and aerospace industriesProximity to NORAD and Space Command operations
Colorado State University-Fort Collins — Fort Collins, CO
Key Distinction: Mandatory capstone group project (DSCI 478) in senior year. Undergraduate research opportunities with Data Science Research Institute
Hakia Insight: CSU's Data Science Research Institute provides undergraduate access to applied projects that many schools reserve for graduate students, giving Fort Collins students publication-ready research credentials before they apply to jobs or advanced programs.
Colorado State University's Bachelor of Science in Data Science is an interdisciplinary program combining mathematics, statistics, and computer science to prepare students for data-driven careers. The 120-credit curriculum spans four years with a strong foundation in core subjects during the first two years, advancing into specialized coursework including a Computer Science concentration. Students gain hands-on experience through mandatory internships, undergraduate research opportunities with the Data Science Research Institute, and a capstone group project in their senior year (DSCI 478). The program emphasizes practical application of data analysis, statistical modeling, and programming in Python and R. An accelerated master's pathway allows completion of both B.S. and M.S. degrees in five years. Graduates achieve an 85% job placement rate within six months of graduation. The program prepares students for roles in machine learning engineering, predictive modeling, data analysis, and AI development across technology, healthcare, finance, retail, and public sectors, with projected 35% employment growth through 2032.
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus. BS
Research Labs and Institutes
- Information Science and Technology Center
- Natural Resource Ecology Laboratory
Industry Partners
- IBM (corporate)
- Hewlett Packard Enterprise (corporate)
- USDA (government)
Admissions
GPA Requirement: 3.0. Application Deadline: April 15.
Requirements: Core mathematics and statistics courses (MATH 156, MATH 256, STAT 315, STAT 341, STAT 342), Computer science foundation (CS 150B, CS 164, CS 165, CS 220), Data science specialization courses (DSCI 100, DSCI 369, DSCI 235, DSCI 320, DSCI 335, DSCI 336, DSCI 445), Capstone group project (DSCI 478), Writing and communication courses, Electives in computer science, data science, and social/behavioral sciences
Location Advantages: Proximity to Denver tech corridorAccess to agricultural and environmental data applications
University of Denver — Denver, CO
Key Distinction: Capstone senior project with real-world data problems. Integration with Ritchie School of Engineering
Hakia Insight: University of Denver's downtown location and direct integration with the Ritchie School of Engineering means data science students can cross-enroll in hardware and robotics courses—practical depth that suburban campuses rarely offer.
The University of Denver's Bachelor of Science in Data Science is housed within the Daniel Felix Ritchie School of Engineering and Computer Science. The program combines rigorous coursework in mathematics, statistics, computer science, and domain-specific applications. Students complete core courses in programming, statistical modeling, machine learning, and data visualization, while choosing electives in areas like business analytics or scientific computing. The curriculum emphasizes hands-on experience through project-based learning and requires a capstone senior project working with real-world data problems. Students have opportunities for undergraduate research with faculty and internships with Denver's growing tech sector. The program leverages Denver's position as a regional technology hub, providing access to industry partnerships and networking opportunities through the university's strong alumni network in data science and analytics fields.
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus. BS
Research Labs and Institutes
- AI for the Public Good Initiative
Industry Partners
- Arrow Electronics (corporate)
- IBM (corporate)
Career Outcomes
Top Employers: Intel.
Notable Faculty
- Dr. Sean Connin — Data Science Graduate Programs
- Dr. Jeffrey Edgington — AI and Data Science
- Dr. Rui Fan — AI and Data Science
- Dr. Mohammad Mahoor — AI and Data Science
- Dr. Chris GauthierDickey — Computer Science, AI integration in education
Admissions
Acceptance Rate: not mentioned%. GPA Requirement: 2.5. Application Deadline: August 22, 2025 (Fall), December 9, 2025 (Winter).
Requirements: Regionally accredited baccalaureate degree, Resume, Two letters of recommendation, Personal statement of at least 300 words
Location Advantages: Downtown Denver locationStrong alumni network in Denver business community
University of Colorado Colorado Springs — Colorado Springs, CO
Key Distinction: Hands-on learning with quadrotor drones and NAO social robots. Flexible curriculum with three selectable tracks to align with student interests
Hakia Insight: UCCS's hands-on labs with drones and NAO robots provide tactile systems-thinking training that pure analytics programs skip, positioning graduates unusually well for robotics, autonomous systems, and computer vision roles in the defense contractors that dominate their region.
The Bachelor of Science in Data Analytics and Systems Engineering combines two complementary fields to prepare students for solving complex, real-world problems. The 128-credit curriculum integrates mathematics through calculus III, computational linear algebra, probability and statistics, and programming sequences with coursework in mechanical engineering, computer science, and electrical engineering. Students select from three track options: a Data Analytics track (18 credits in operations research, algorithms, data visualization, data mining, machine learning), a Systems Engineering track (18 credits in systems engineering, optimization, project design, mechanical systems, electronics), or a General track (9 credits each in both areas). The program uses hands-on learning with practical systems including quadrotor drones and NAO social robots. Graduates pursue diverse roles as data analysts, data scientists, business intelligence analysts, data engineers, systems engineers, integration engineers, and DevOps engineers across multiple industries.
Programs Offered
- Bachelor of Science in Data Analytics and Systems Engineering — 4 years, on-campus. BS
Research Labs and Institutes
- Distributed, Sustainable, and Cloud Computing Systems (DISCO) Lab
- Games and Media Integration (GMI) Lab
- Vision and Security Technology (VAST) Lab
- Language Information and Computation (LINC) Lab
- Network Security (NETSEC) Lab
Industry Partners
- Lockheed Martin (corporate)
- Northrop Grumman (corporate)
Career Outcomes
Top Employers: Intel.
Notable Faculty
- Terrance Boult — Computer vision, image processing, networking and medical imaging
- Jugal Kalita — Artificial intelligence, bioinformatics, information retrieval, natural language processing and machine learning
- Xiaobo Zhou — Cloud Computing and BigData Processing
Location Advantages: Proximity to defense and aerospace industriesAccess to military installations for research partnerships
Metropolitan State University of Denver — Denver, CO
Key Distinction: Faculty-led undergraduate research projects. Hackathons and programming competitions
Hakia Insight: MSU Denver's emphasis on faculty-led research and hackathons compensates for lower name recognition by building a competitive resume early—particularly valuable for a public urban school where peer networks are less automatic than at flagship campuses.
The B.S. in Data Science and Machine Learning at MSU Denver provides cutting-edge skills in machine learning, data science, and statistics through a well-rounded curriculum. Students develop expertise in algorithms, data analysis, and predictive modeling to deploy ML-based software systems and transform data into actionable insights. The program emphasizes hands-on experience through programming competitions, hackathons, and Kaggle data science competitions. Students can engage in faculty-led undergraduate research projects and participate in open-source machine learning software development. Career preparation includes job fairs, mock interviews, and networking through the Classroom to Career Hub. Graduates commonly find positions in aerospace and defense, telecommunications, and technology and software sectors. Unique opportunities include ACM student chapter participation, conference presentations, and collaborative projects with local civic organizations.
Programs Offered
- Bachelor of Science in Data Science and Machine Learning — 4 years, on-campus. BS
Industry Partners
- Aerospace and Defense (employer)
- Telecommunications (employer)
- Technology and Software (employer)
Career Outcomes
Top Employers: Aerospace and Defense companies, Telecommunications companies, Technology and Software companies.
Accreditations and Certifications
- Higher Learning Commission accredited
Location Advantages: Downtown Denver locationAccess to Colorado's Front Range technology corridorLocated in Denver, ColoradoAccess to aerospace and defense industryProximity to telecommunications companiesAccess to technology and software companies
Regis University — Denver, CO
Key Distinction: Senior capstone project with real-world datasets. Small class sizes with personalized faculty mentorship
Hakia Insight: Regis's small class sizes and personalized mentorship model is uncommon in data science (where cohorts often exceed 100), creating genuine relationships with faculty who can write detailed recommendation letters—a quiet advantage for students targeting specialized roles.
Regis University's Bachelor of Science in Data Science program combines rigorous mathematical foundations with practical programming skills and business applications. The curriculum integrates statistics, computer science, and domain expertise through hands-on projects using industry-standard tools like Python, R, and SQL. Students complete a comprehensive capstone project in their senior year, working with real-world datasets to solve complex problems. The program emphasizes ethical data practices and critical thinking, preparing graduates for immediate entry into the workforce. Small class sizes foster close faculty mentorship and collaborative learning. Internship opportunities are strongly encouraged, with connections to Denver-area employers in healthcare, finance, and technology sectors.
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus. BS
Career Outcomes
Top Employers: Intel.
Notable Faculty
- Kellen Sorauf — Department Chair, Associate Professor
- Abigail Schneider — Associate Professor and Director of the Sustainable Economic and Enterprise Development (SEED) Institute
- Kelly Miller — Assistant Professor
- R. Craig Briggs — Assistant Professor
- Matjaž Bren — Lecturer
- Rod Thirion — Lecturer
Accreditations and Certifications
- Higher Learning Commission accredited
Location Advantages: Denver metropolitan area accessProximity to Colorado technology industry
Best Master's Data Science Degree Programs in Colorado
Colorado Technical University-Colorado Springs — Colorado Springs, CO
Key Distinction: Designed for working professionals. Flexible scheduling
Hakia Insight: Colorado Tech's master's program is explicitly designed for working professionals with flexible scheduling, but the limited data on outcomes and employer diversity suggests it's a credential-stacking option rather than a career-redefining degree.
Colorado Technical University-Colorado Springs' Master of Science in Data Science is designed as a career-focused program for working professionals seeking to advance in the rapidly growing field of data analytics. The program typically emphasizes practical, industry-relevant skills including statistical analysis, machine learning, data visualization, and big data technologies. As a career-oriented institution, CTU likely offers flexible scheduling options including online and hybrid formats to accommodate working adults. The curriculum generally focuses on applied learning with real-world projects rather than theoretical research, making it ideal for professionals looking to transition into data science roles or advance their current careers. Students can expect to work with industry-standard tools and technologies while developing competencies in data mining, predictive modeling, and business intelligence to meet employer demands in various industries.
Programs Offered
- Master of Science in Data Science — 1-2 years, on-campus. MS
Career Outcomes
Top Employers: Intel.
Location Advantages: Proximity to Colorado Springs aerospace and defense contractorsAccess to growing Colorado tech corridor
University of Colorado Boulder — Boulder, CO
Key Distinction: Two admission pathways: Direct to Data Science (30 credits for strong quantitative/programming backgrounds) and Bridge to Data Science (30–34 credits with up to 7 credits of foundational courses in statistics, R programming, and Python). Non-thesis format focused on applied coursework; optional capstone (DTSC 5810) or independent study (DTSC 5840) allows practical application
Hakia Insight: CU Boulder's dual-pathway admissions (Direct and Bridge tracks) is unusually transparent about prerequisite gaps, and the optional capstone design lets experienced engineers skip frivolous projects—a pragmatic structure for professionals who already know their domain.
The Master of Science in Data Science at CU Boulder is a non-thesis, 30-credit program designed for working professionals seeking advanced skills in statistical analysis, machine learning, data mining, and big data architecture. Students choose between the Direct to Data Science Pathway (30 credits for those with strong math and programming backgrounds) or the Bridge to Data Science Pathway (30-34 credits for those needing foundational coursework). The program emphasizes practical competencies: acquiring and cleaning data, analyzing large datasets, designing statistical experiments, and communicating results to non-technical audiences. Most students complete the degree in 1.5–2 years, with a 4-year maximum time limit. The curriculum includes 21 credits of core coursework in statistics, computer science, and data science fundamentals, plus 9 credits of electives spanning machine learning, cybersecurity, NLP, computer vision, and domain-specific applications. Optional capstone or independent study projects (up to 3 credits) allow students to apply learning to real-world problems. Graduates advance into data scientist, machine learning engineer, and analytics leadership roles with mid-career salary potential of $110,000–$130,000+, representing significant advancement over bachelor's-level positions.
Programs Offered
- Master of Science in Data Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- Institute of Cognitive Science
- Cooperative Institute for Research in Environmental Sciences
- BioFrontiers Institute
Industry Partners
- Google (corporate)
- IBM (corporate)
- NIST (government)
- NOAA (government)
Notable Faculty
- Claire Monteleoni — Machine learning and climate informatics
- Jordan Boyd-Graber — Natural language processing
Admissions
GPA Requirement: 2.75 minimum (3.2+ recommended). Application Deadline: See Graduate School Admissions Deadlines.
Requirements: 21 credits core coursework: Statistics (STAT 5000, 5010, 5600), Computer Science (DTSC 5501, CSCI 5502, CSCI 5622), General Data Science (DTSC 5301, 5302, 5303), 9 credits elective coursework from approved list, No comprehensive final examination required, Optional capstone or independent study project
Location Advantages: Access to Denver tech corridorBoulder startup ecosystemProximity to federal research labs
Colorado School of Mines — Golden, CO
Key Distinction: Non-thesis track — coursework-based degree. Fully online option available alongside on-campus delivery
Hakia Insight: Mines' fully online master's option paired with non-thesis coursework is designed for embedded engineers at energy companies, making it a credential-within-employment rather than a transition program—a deliberate choice with narrow but deep market fit.
The Master of Data Science is a non-thesis program designed for working professionals seeking to advance their careers in data science. The program balances foundational coursework in statistics and computer science with individualized, domain-specific electives, allowing students to tailor their focus to their industry or application area. Offered in both on-campus and fully online formats, the 30-credit program can typically be completed in 2 years part-time. The curriculum emphasizes professional development through embedded courses in research ethics, leadership, teamwork, and oral communication. Students can specialize in areas such as electrical engineering, geophysics, business analytics, or petroleum data analytics. The program prepares graduates for data science careers in industry and government while maintaining flexibility for those considering PhD study. Career advancement outcomes position graduates for roles in machine learning engineering, data analytics leadership, and specialized domain roles with mid-career salary growth potential typical of advanced technical degrees.
Programs Offered
- Master of Data Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- Center for Wave Phenomena
- Payne Institute for Public Policy
Industry Partners
- ExxonMobil (corporate)
- Chevron (corporate)
- Schlumberger (corporate)
- ConocoPhillips (corporate)
Accreditations and Certifications
- Higher Learning Commission accredited
- ABET accredited
Location Advantages: Proximity to Denver tech corridorAccess to National Renewable Energy LaboratoryStrong connections to Colorado energy industry
Regis University — Denver, CO
Key Distinction: Practicum-based capstone (two applied projects) instead of thesis requirement. Optional Data Engineering specialization with specialized courses in data wrangling, big data architecture, SQL/NoSQL, and engineering-focused practicum
Hakia Insight: Regis's optional Data Engineering specialization teaches SQL, NoSQL, and big data architecture alongside data science theory—most programs treat these as afterthoughts, leaving graduates unqualified for pipeline and infrastructure roles that often pay $15K–$25K more.
Regis University's Master of Science in Data Science is a 36-credit program designed for working professionals seeking expertise in data discovery and analysis with emphasis on social responsibility aligned with Jesuit values. The program offers a practicum-based completion requirement (two capstone courses: Data Science Practicum I and II) rather than a traditional thesis option, allowing students to apply learning to real-world data problems. An optional Data Engineering specialization is available, enabling students to deepen expertise in data collection, preparation, wrangling, and big data architecture. The curriculum integrates ethics, privacy, and social justice considerations throughout, addressing societal concerns about data use. While specific part-time scheduling, evening/weekend availability, assistantship stipends, and embedded professional certifications are not detailed in the catalog, the practicum structure suggests applied, career-focused learning. Career advancement outcomes and salary data specific to this program are not provided in the source material.
Programs Offered
- Master of Science in Data Science — 1-2 years, on-campus. MS
Notable Faculty
- Kellen Sorauf — Department Chair, Associate Professor
- Abigail Schneider — Associate Professor and Director of the Sustainable Economic and Enterprise Development (SEED) Institute
- Kelly Miller — Assistant Professor
- R. Craig Briggs — Assistant Professor
- Matjaž Bren — Lecturer
- Rod Thirion — Lecturer
Accreditations and Certifications
- Higher Learning Commission accredited
Location Advantages: Denver metropolitan area accessProximity to Colorado technology industry
University of Colorado Denver/Anschutz Medical Campus — Denver, CO
Key Distinction: Thesis vs non-thesis track options with maximum coursework flexibility. Multiple concentration areas including Data Science and Applied Statistics
Hakia Insight: CU Denver's partnership with the Center for Health AI and University of Colorado Hospital creates rare access to real medical datasets during coursework, meaning graduates enter healthcare analytics roles with institutional relationships already in place—a credential that typically requires years of external networking.
The Master of Science in Applied Mathematics at CU Denver offers flexible specialization options including Data Science, Applied Statistics, Applied Probability, and Operations Research. The program is designed for working professionals seeking contemporary education in data science and quantitative analysis. Students can tailor coursework with maximum flexibility or specialize in a concentration area. The program emphasizes employer-valued skills including problem solving, critical thinking, data analysis, and quantitative reasoning. Students participate in real-world research through the Math Clinic and Statistical Consulting workshop, collaborating with internationally recognized scholars on projects including machine learning, optimization, and data analysis. Many MS graduates have advanced into employment in Denver's business and research sectors.
Programs Offered
- Master of Science in Applied Mathematics — 1-2 years, on-campus. MS
Research Labs and Institutes
- Center for Health AI
- Colorado Clinical and Translational Sciences Institute
Industry Partners
- University of Colorado Hospital (government)
- Children's Hospital Colorado (nonprofit)
Notable Faculty
- Farnoush Banaei-Kashani — Data science, big data management and mining, spatiotemporal data management, graph data mining
Location Advantages: Integrated medical campus with major hospitalsAccess to healthcare and pharmaceutical industry in Denver metro
Colorado State University-Fort Collins — Fort Collins, CO
Key Distinction: Available in on-campus and online formats for working professionals. Accelerated Master's Program (AMP) pathway for eligible candidates enabling completion in less time at significant cost savings
Hakia Insight: CSU's Accelerated Master's Program (AMP) pathway and dual online/on-campus delivery is built for remote workers and domestic professionals, while the Data Science Specialization within Applied Statistics keeps tuition competitive—a low-friction option for career pivots that don't require a prestigious brand.
Colorado State University's Master of Applied Statistics (M.A.S.) with Data Science Specialization prepares working professionals for advanced analytics careers. The program is available in on-campus and online formats, offering flexibility for employed students. The Department of Statistics consistently ranks in the top 50 nationally. The M.A.S. program emphasizes applied coursework and practical data science skills. Graduate assistantship opportunities and financial aid options are available through the department. The accelerated master's program pathway enables completion in less time at significant cost savings for eligible candidates. While specific thesis vs. coursework track details, salary advancement figures, embedded professional certifications, and employer tuition partnerships are not detailed in this content, prospective students should contact the department representative for comprehensive information on these working professional considerations.
Programs Offered
- Master of Applied Statistics (M.A.S.) - Data Science Specialization — 1-2 years, on-campus. M.A.S.
Research Labs and Institutes
- Information Science and Technology Center
- Natural Resource Ecology Laboratory
Industry Partners
- IBM (corporate)
- Hewlett Packard Enterprise (corporate)
- USDA (government)
Admissions
GPA Requirement: 3.0. Application Deadline: April 15.
Requirements: Coursework and credit requirements specified in Colorado State University general catalog
Location Advantages: Proximity to Denver tech corridorAccess to agricultural and environmental data applications
University of Denver — Denver, CO
Key Distinction: Hybrid schedule with seamless transition between online and on-campus learning. Fully online option available
Hakia Insight: University of Denver's 2.5 GPA floor and hybrid model attract career-switchers, but the real differentiator is the AI for the Public Good Initiative—students work on applied problems for nonprofits and civic institutions, building portfolios that signal social impact alongside technical chops to employers like IBM.
The Master of Science in Applied Data Science and AI from University of Denver offers exceptional flexibility for working professionals with hybrid and fully online options, allowing seamless transitions between formats. The 18-24 month program features 36-48 credit hours with no GRE requirement and multiple start dates (Fall/Winter). Students can fast-track completion by transferring up to 12 credits from industry certifications like Oracle. The curriculum integrates AI modeling, machine learning, data engineering, and neural networks with real-world applications. Optional for-credit internships provide hands-on experience, while comprehensive career services include coaching, job search support, and networking. Graduates secure high-demand roles with a median salary of $112k, working at top companies across technology, finance, healthcare, and consulting sectors. The program emphasizes ethical AI use and builds project-based portfolios to showcase skills.
Programs Offered
- Master of Science in Applied Data Science and AI — 1-2 years, on-campus. MS
Research Labs and Institutes
- AI for the Public Good Initiative
Industry Partners
- Arrow Electronics (corporate)
- IBM (corporate)
Career Outcomes
Median Salary: $NaN.
Notable Faculty
- Dr. Sean Connin — Data Science Graduate Programs
- Dr. Jeffrey Edgington — AI and Data Science
- Dr. Rui Fan — AI and Data Science
- Dr. Mohammad Mahoor — AI and Data Science
- Dr. Chris GauthierDickey — Computer Science, AI integration in education
Admissions
Acceptance Rate: not mentioned%. GPA Requirement: 2.5. Application Deadline: August 22, 2025 (Fall), December 9, 2025 (Winter).
Requirements: Regionally accredited baccalaureate degree, Resume, Two letters of recommendation, Personal statement of at least 300 words
Location Advantages: Downtown Denver locationStrong alumni network in Denver business community
University of Colorado Colorado Springs — Colorado Springs, CO
Key Distinction: Flexible scheduling for working professionals. Capstone project with real-world applications
Hakia Insight: While Lockheed Martin and Northrop Grumman partnerships are expected for Colorado Springs, the DISCO Lab's focus on distributed systems gives students direct access to infrastructure problems that defense contractors actually hire for—a narrower aperture than generic 'machine learning' but far more specific to the region's $40B defense sector.
The Master of Science in Data Science at University of Colorado Colorado Springs is designed to prepare students for advanced careers in data analytics and machine learning. The program typically combines rigorous coursework in statistics, programming, and machine learning with practical applications across various industries. Students can expect to work with tools like Python, R, SQL, and big data platforms while developing skills in data visualization, predictive modeling, and statistical analysis. The curriculum often includes capstone projects that allow students to apply their knowledge to real-world problems. Designed for both recent graduates and working professionals, the program offers flexible scheduling options to accommodate various lifestyles. Graduates are prepared for leadership roles in data science, analytics consulting, and research positions across technology, healthcare, finance, and government sectors.
Programs Offered
- Master of Science in Data Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- Distributed, Sustainable, and Cloud Computing Systems (DISCO) Lab
- Games and Media Integration (GMI) Lab
- Vision and Security Technology (VAST) Lab
- Language Information and Computation (LINC) Lab
- Network Security (NETSEC) Lab
Industry Partners
- Lockheed Martin (corporate)
- Northrop Grumman (corporate)
Career Outcomes
Top Employers: Intel.
Notable Faculty
- Terrance Boult — Computer vision, image processing, networking and medical imaging
- Jugal Kalita — Artificial intelligence, bioinformatics, information retrieval, natural language processing and machine learning
- Xiaobo Zhou — Cloud Computing and BigData Processing
Location Advantages: Proximity to defense and aerospace industriesAccess to military installations for research partnerships
Best Doctoral Data Science Degree Programs in Colorado
University of Colorado Boulder — Boulder, CO
Key Distinction: 20 core faculty and 25 affiliated faculty from other departments. co-advising opportunities with affiliate faculty
Hakia Insight: CU Boulder's 45 faculty (20 core + 25 affiliated) creates an unusual advantage for applied math PhDs: you can co-advise across Institute of Cognitive Science and BioFrontiers simultaneously, letting you build hybrid expertise in climate informatics or cognitive AI that most programs silently forbid.
The Applied Mathematics doctoral program at CU Boulder offers extensive research opportunities through 20 core faculty and 25 affiliated faculty from other departments, providing unique interdisciplinary collaboration. Students can explore research in computational mathematics, mathematical biology, mathematical geosciences, applied nonlinear PDEs, statistics and data science, and stochastic processes. The program emphasizes tailored educational experiences through close faculty-student interaction and co-advising opportunities. Students have access to world-class research institutes in Boulder including the National Center for Atmospheric Research, National Institute of Standards and Technology, NOAA, National Renewable Energy Lab, and Laboratory for Atmospheric and Space Physics. The department maintains a strong commitment to diversity and provides virtual information sessions for prospective students. However, specific details about funding packages, time to degree, publication expectations, and post-graduation placement rates are not provided on this page.
Programs Offered
- Doctor of Philosophy in Applied Mathematics — 4-6 years, on-campus. PhD
Research Labs and Institutes
- Institute of Cognitive Science
- Cooperative Institute for Research in Environmental Sciences
- BioFrontiers Institute
Industry Partners
- Google (corporate)
- IBM (corporate)
- NIST (government)
- NOAA (government)
Notable Faculty
- Claire Monteleoni — Machine learning and climate informatics
- Jordan Boyd-Graber — Natural language processing
Admissions
GPA Requirement: 2.75 minimum (3.2+ recommended). Application Deadline: See Graduate School Admissions Deadlines.
Requirements: comprehensive exam, dissertation defense
Location Advantages: Access to Denver tech corridorBoulder startup ecosystemProximity to federal research labs
Colorado State University-Fort Collins — Fort Collins, CO
Key Distinction: Full funding packages: $41,000/year or $1,969/month stipend + tuition waiver + health insurance. 3-4 years guaranteed funding through GRA/GTA positions
Hakia Insight: Colorado State's $41K/year stipend guarantee through 3-4 years removes the feast-or-famine funding roulette of many PhD programs, but more strategically—this stability funds students to work on long-horizon environmental data problems with USDA and the Natural Resource Ecology Lab, not just chase quick papers.
The Department of Ecosystem Science and Sustainability at Colorado State University offers PhD programs in Watershed Science and Ecosystem Science focusing on environmental research. PhD students receive 3-4 years of funding support through Graduate Research Assistant (GRA) and Graduate Teaching Assistant (GTA) positions at $41,000/year for certain positions and $1,969 monthly for others. Funding packages include full tuition waiver and health insurance coverage. Research areas span wetland remote sensing, water governance, agricultural modeling, and climate adaptation. The program requires field data collection, stakeholder engagement, and scientific publication. Students conduct interdisciplinary research on water resources, ecosystem dynamics, and sustainability challenges. The department emphasizes collaboration with leading water and sustainability scientists, preparing graduates for careers in government agencies, private industry, academia, and research institutions.
Programs Offered
- PhD in Watershed Science / PhD in Ecosystem Science and Sustainability — 4-6 years, on-campus. PhD
Research Labs and Institutes
- Information Science and Technology Center
- Natural Resource Ecology Laboratory
Industry Partners
- IBM (corporate)
- Hewlett Packard Enterprise (corporate)
- USDA (government)
Admissions
GPA Requirement: 3.0. Application Deadline: April 15.
Requirements: Original research dissertation, Field data collection, Human subjects research protocols, Scientific publication
Location Advantages: Proximity to Denver tech corridorAccess to agricultural and environmental data applications
Colorado School of Mines — Golden, CO
Key Distinction: Colorado School of Mines uniquely specializes in data science applications to earth sciences, energy systems, and natural resource industries.
Hakia Insight: Colorado School of Mines' doctoral specialization in energy systems and earth sciences data science is niche enough to be overlooked, yet deep enough that graduates command premium roles at ExxonMobil and NREL—students get geophysics-grade technical rigor applied to $100B+ industries most CS programs never touch.
At the doctoral level, data science at Colorado School of Mines benefits from the institution's deep technical foundation in engineering and applied sciences, creating a program that emphasizes quantitative rigor and real-world problem-solving. The curriculum integrates data science with domain expertise in mining, energy, and environmental engineering—allowing students to work on high-stakes computational challenges like resource optimization, climate modeling, and subsurface characterization. What distinguishes this program is its project-based learning model, where students apply machine learning and statistical methods to actual industry datasets and collaborate with faculty researchers on funded projects. The school's location in Golden positions students for internships and permanent roles with major energy companies, mining operations, and technology firms focused on industrial applications. Faculty members bring expertise spanning computational geoscience, machine learning for engineering systems, and predictive analytics. Graduates emerge with both strong programming fundamentals and domain knowledge that makes them immediately valuable in sectors like energy transition, resource management, and climate tech—areas experiencing significant growth and investment. The program's small class sizes ensure close mentorship and access to specialized computing resources, including high-performance clusters used for research.
Programs Offered
- Doctor of Philosophy in Data Science — 4-6 years, on-campus
- Doctor of Science in Data Science — 4-6 years, online
Research Labs and Institutes
- Center for Wave Phenomena
- Payne Institute for Public Policy
Industry Partners
- ExxonMobil (corporate)
- Chevron (corporate)
- Schlumberger (corporate)
- ConocoPhillips (corporate)
Career Outcomes
Median Salary: $NaN. Top Employers: ExxonMobil, Chevron, ConocoPhillips, Schlumberger, National Renewable Energy Laboratory.
Accreditations and Certifications
- Higher Learning Commission accredited
- ABET accredited
Location Advantages: Proximity to Denver tech corridorAccess to National Renewable Energy LaboratoryStrong connections to Colorado energy industry
University of Denver — Denver, CO
Key Distinction: DU offers a personalized, private university approach to data science education with strong business applications focus.
Hakia Insight: DU's private-university model and downtown Denver location mean your doctoral cohort includes working professionals from the regional banking and finance sectors, creating a natural mentorship ecosystem that public universities can't replicate and yielding faster pathways to industry advisory board roles.
At the doctoral level, the University of Denver offers data science programs through its Daniel Felix Ritchie School of Engineering and Computer Science. As a private research university, DU provides smaller class sizes and more personalized attention compared to larger state institutions. The program combines computer science, statistics, and business applications, reflecting DU's strong business school connections. The university has been investing in modern facilities and technology infrastructure to support data science education. DU's location in Denver provides access to a growing tech industry and numerous internship opportunities. The program emphasizes both theoretical foundations and practical applications, with opportunities for students to work on real-world projects with local businesses and organizations. The university's strong alumni network in the Denver area provides additional career opportunities for graduates.
Programs Offered
- Doctor of Philosophy in Data Science — 4-6 years, on-campus
- Doctor of Science in Data Science — 4-6 years, online
Research Labs and Institutes
- AI for the Public Good Initiative
Industry Partners
- Arrow Electronics (corporate)
- IBM (corporate)
Notable Faculty
- Dr. Sean Connin — Data Science Graduate Programs
- Dr. Jeffrey Edgington — AI and Data Science
- Dr. Rui Fan — AI and Data Science
- Dr. Mohammad Mahoor — AI and Data Science
- Dr. Chris GauthierDickey — Computer Science, AI integration in education
Admissions
Acceptance Rate: not mentioned%. GPA Requirement: 2.5. Application Deadline: August 22, 2025 (Fall), December 9, 2025 (Winter).
Requirements: Regionally accredited baccalaureate degree, Resume, Two letters of recommendation, Personal statement of at least 300 words
Location Advantages: Downtown Denver locationStrong alumni network in Denver business community
