Bachelor's Machine Learning Programs in North Carolina
University of North Carolina at Chapel Hill — Chapel Hill, NC
Key Distinction: The curriculum provides in-depth exposure to quantitative topics and opportunities for direct application through four-course concentrations, upper-level electives, mentored research, and internship opportunities with a focus on ethical practice and responsible data science.
Hakia Insight: UNC Chapel Hill's emphasis on four-course concentrations and ethical practice, backed by faculty like Kristen Hassmiller Lich who research AI fairness, means graduates can articulate both technical depth and responsible AI principles—increasingly non-negotiable for roles at companies facing regulatory pressure.
At the bachelor's level, the bachelor of science (B.S.) in data science provides students with a strong foundation in preparation for entry to the workforce or pursuit of an advanced degree. The B.S. in data science is comprised of six competencies: responsible data science, communication, computational thinking, mathematical and statistical foundations, optimization, and machine learning and artificial intelligence (AI).
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Notable Faculty
- Dr. Kristen Hassmiller Lich — artificial intelligence, machine learning and data science
- Dr. Lisa M. LaVange — artificial intelligence, machine learning and data science
- Dr. Kari North — artificial intelligence, machine learning and data science
- Dr. Hongtu Zhu — artificial intelligence, machine learning and data science
Admissions
GPA Requirement: 2.000.
Requirements: MATH 231 Calculus of Functions of One Variable I, MATH 232 Calculus of Functions of One Variable II, MATH 233 Calculus of Functions of Several Variables, MATH 347 Linear Algebra for Applications, MATH 381 Discrete Mathematics, STOR 120 Foundations of Statistics and Data Science
Location Advantages:
Duke University — Durham, NC
Key Distinction: Duke's unique immersive environment focuses on turning AI models into market-ready products through hands-on learning with real datasets, users, and engineering pipelines from the first semester, blending AI, full-stack software, product strategy and responsible innovation.
Hakia Insight: Duke's AIPI program front-loads real datasets and engineering pipelines from semester one, not senior year; combined with a $118K median salary and OpenAI/Samsung placements, this signals employers reward students who've shipped products over those who've only built proofs-of-concept.
At the bachelor's level, duke's AIPI (Artificial Intelligence for Product Innovation) Master of Engineering program prepares students with strong technical AI skills complemented by hands-on practical experience to build AI applications that solve real problems. The program combines technical AI/ML coursework with business courses and capstone projects to develop leadership skills for AI product innovation.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Athena NSF AI Institute
- ASIC NSF IUCRC
- Rhodes Information Initiative at Duke (iiD)
- Duke AI Health
Industry Partners
- OpenAI (tech)
- Samsung (tech)
- Microsoft (tech)
- IBM (tech)
- Target (retail)
- Eli Lilly (healthcare)
- Grubhub (tech)
- DoorDash (tech)
- Fidelity (finance)
- Intuit (tech)
- Autodesk (tech)
- Qualcomm (tech)
- Intel (tech)
- Facebook (tech)
- HP (tech)
Career Outcomes
Median Salary: $118,000. Top Employers: OpenAI, Target, Eli Lilly, Samsung, IBM, DoorDash, Fidelity, Intuit, Autodesk.
Notable Faculty
- Jon Reifschneider — Executive Director, AI for Product Innovation
- Brinnae Bent — Executive in Residence
- Hai Li — Chair of ECE, AI/ML Hardware
- Lawrence Carin — AI/ML Applications
- Cynthia D. Rudin — Machine Learning
- Yiran Chen — AI Hardware
Location Advantages:
University of North Carolina at Charlotte — Charlotte, NC
Key Distinction: Offers both engineering-focused machine learning concentration and applied AI certificate that can be pursued concurrently with any graduate degree program at the university
Hakia Insight: UNC Charlotte's dual-pathway model—both engineering-focused ML concentration and applied AI certificate—lets students pursue concurrent credentials without degree stacking, a practical advantage for working professionals who need flexibility without academic bloat.
At the bachelor's level, UNC Charlotte offers machine learning education through multiple pathways including an undergraduate concentration in Machine Learning within ECE programs and a graduate certificate in Applied Artificial Intelligence. The programs focus on training students in machine learning theory, design, and synthesis of intelligent machines capable of autonomous learning.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Notable Faculty
- Dr. Andrew Willis — Machine Learning (Associate Professor of ECE, Faculty contact for ML concentration)
Admissions
GPA Requirement: 2.5.
Requirements: first-year engineering curriculum, two semesters of calculus, one semester of discrete structures, working knowledge of two higher-level programming languages
Location Advantages:
North Carolina State University at Raleigh — Raleigh, NC
Key Distinction: Interdisciplinary approach combining Statistics, Mathematics, and Computer Science with project-based learning, strong faculty research in interpretable AI, and industry partnerships through labs like CAEML
Hakia Insight: NC State's dual B.S./B.A. structure across Statistics, ECE, and interdisciplinary departments is rare—most competitors force students into one silo, but here you can customize interpretable AI focus through labs like iVMCL while simultaneously accessing Oak Ridge and HPE partnership projects.
At the bachelor's level, NC State offers machine learning through multiple departments including Statistics, Electrical and Computer Engineering, and an interdisciplinary Master's in Foundations of Data Science. The programs focus on developing intelligent systems, algorithms that learn from data, and methods that turn data into knowledge.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Laboratory for interpretable Visual Modeling, Computing and Learning (iVMCL)
- Center for Advanced Electronics through Machine Learning (CAEML)
- Optical Sensing Lab (OSL)
- Active Robotics Sensing (AROS)
Industry Partners
- Oak Ridge National Laboratory (government research)
- USDA (government agriculture)
- Hewlett Packard Enterprise (technology)
Notable Faculty
- Dr. Jessie Jeng — machine learning statistics
- Dr. Tianfu Wu — machine learning and AI
- Dr. Hamid Krim — signal processing and learning
- Dr. Edgar Lobaton — machine learning applications
- Dr. Mansoor Haider — data science program director
Admissions
GPA Requirement: 3.00.
Requirements: single variable calculus, matrix or linear algebra, multivariable calculus preferred, probability and statistics preferred, data structures or algorithms preferred
Accreditations and Certifications
Location Advantages:
Davidson College — Davidson, NC
Key Distinction: A liberal arts machine learning program that combines technical rigor with ethical reasoning and interdisciplinary perspectives, emphasizing small-scale mentorship and undergraduate research.
Hakia Insight: Davidson's proximity to Charlotte's fintech corridor means your ML coursework in ethics and reasoning isn't theoretical—you're 30 minutes from Capital One, Bank of America, and Wells Fargo hiring pipelines that explicitly value liberal arts-trained technologists who can explain model decisions to non-technical stakeholders.
At the bachelor's level, davidson College's computer science program takes a liberal arts approach to machine learning and artificial intelligence, embedding technical depth within a broader educational context that emphasizes critical thinking and ethical reasoning. The curriculum covers machine learning fundamentals, statistical methods, and practical applications while maintaining the hallmark Davidson emphasis on small classes, close faculty mentorship, and integration with humanities and social sciences perspectives on technology. Advanced students pursue independent research projects in machine learning, often collaborating directly with faculty on investigations spanning computer vision, natural language processing, and data analysis. The college's location near Charlotte, North Carolina—a major financial and tech hub—facilitates internships and recruiting connections with major corporations and fintech firms. Davidson graduates in computer science and related fields consistently pursue graduate study at top-tier universities and careers at leading technology companies, with the program's emphasis on communication, ethics, and interdisciplinary thinking distinguishing its graduates in competitive job markets. The intimate scale of the liberal arts setting allows students to develop machine learning expertise without losing sight of broader questions about technology's role in society.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Proximity to Charlotte financial and tech sectorAccess to major corporations and fintech firms for internships and recruiting
Wake Forest University — Winston-Salem, NC
Key Distinction: Wake Forest's ML program differentiates itself through intensive small-cohort learning and direct faculty mentorship in a research-active environment positioned within the Research Triangle's strong tech ecosystem.
Hakia Insight: Wake Forest's real advantage isn't the Research Triangle location—it's the 30-mile radius that creates a self-reinforcing ecosystem where IBM Research Park, Cisco, and Google actively recruit from small cohorts, and faculty like Errin Fulp teach machine learning security applications that those companies immediately hire for.
At the bachelor's level, wake Forest's machine learning program emphasizes a rigorous mathematical foundation paired with practical application in a close-knit learning environment. The curriculum integrates core ML theory with hands-on projects in computer vision, natural language processing, and reinforcement learning, supported by faculty who actively engage students in their research. What distinguishes the experience is the school's commitment to small class sizes and direct mentorship—students work closely with professors rather than being one of hundreds in a lecture hall. The program leverages Wake Forest's location in the Research Triangle region, providing proximity to major tech companies and research institutions while maintaining the undergraduate-focused liberal arts ethos. Internship and capstone opportunities connect students to real-world machine learning challenges in healthcare, finance, and software development. The program attracts students seeking depth in mathematical foundations (linear algebra, probability, optimization) without sacrificing breadth across ML subdisciplines. Graduate placement has historically been strong in both tech companies and specialized ML roles, with alumni moving into positions at major cloud providers, financial firms, and AI-focused startups. The combination of theoretical rigor, personalized advising, and regional industry access makes this particularly valuable for students who thrive with faculty accessibility and want to build strong fundamentals before specializing.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Wake Forest Computer Science Department Labs
Industry Partners
- IBM (corporate)
- Cisco (corporate)
- Google (corporate)
Career Outcomes
Top Employers: Google, Microsoft, Amazon, Capital One, Cisco.
Notable Faculty
- Barry Kapron — Theoretical computer science, computability theory
- Errin Fulp — Cybersecurity, network security, machine learning applications to security
Accreditations and Certifications
- ABET accredited (Computer Science)
Location Advantages: Research Triangle proximity—within 30 miles of IBM Research Triangle Park, Cisco, Google, and Duke/UNC research centersStrong regional tech ecosystem with opportunities at established companies and emerging startupsAccess to healthcare and biotech companies in the Triangle region
North Carolina A & T State University — Greensboro, NC
Key Distinction: North Carolina A&T is the only university in North Carolina offering a stand-alone bachelor's degree in Artificial Intelligence, while most other institutions only offer AI as a concentration within computer science degrees.
Hakia Insight: While NC State, UNC, and Duke offer AI concentrations, NC A&T's stand-alone B.S. in Artificial Intelligence (Applied Track) means you graduate with a degree that names your expertise directly—a credential advantage when competing for roles at companies that screen by degree title before reviewing coursework.
North Carolina A&T State University offers a groundbreaking Bachelor of Science in Artificial Intelligence (Applied Track) through the Department of Computer Systems and Technology, making it the only stand-alone AI bachelor's degree in North Carolina and one of only a handful nationally. This interdisciplinary program integrates core principles of computer systems, robotics, machine learning, and data science with real-world applications. Students can choose from specialized concentrations in Robotics, Artificial Intelligence, and Machine Learning. The program emphasizes applied learning through project-based coursework, internships, and research collaborations, with support from cutting-edge laboratories and industry partnerships. The university also offers complementary graduate programs including MS in Applied Mathematics and Data Analytics, PhD in Computational Data Science and Engineering, and MS in Data Science and Engineering, creating a comprehensive ML/AI educational ecosystem.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Center for Trustworthy AI (CTA)
- CASIS - Center for Academic Studies in Identity Sciences
- Center for Cyber Defense
- Cyber Defense and AI Lab
Notable Faculty
- Dr. Evelyn Sowells-Boone — Computer Systems Technology
- Dr. Ahmad Patooghy — Artificial Intelligence
- Dr. Kaushik Roy — Trustworthy AI, Cybersecurity, Adversarial Machine Learning
- Dr. Xiaohong Yuan — Biometrics, Identity Sciences, Cyber Systems
Admissions
GPA Requirement: 3.0.
Requirements: Calculus I and II, Differential Equations, Linear Algebra, upper division math course
Accreditations and Certifications
- National Center of Academic Excellence in Information Assurance Education designated by NSA and Department of Homeland Security
Location Advantages:
University of North Carolina Wilmington — Wilmington, NC
Key Distinction: UNCW offers North Carolina's first Intelligent Systems Engineering Bachelor of Science program and features an accelerated 16-month Master's in Data Science & Artificial Intelligence with 70% of students obtaining summer internships between their first and second years.
Hakia Insight: UNCW's 16-month accelerated master's pipeline with 70% summer internship placement between years one and two compresses what takes peers two years into a 16-month sprint, meaning you're earning and building real projects 6-12 months earlier than classmates still in first-year coursework.
At the bachelor's level, the University of North Carolina Wilmington offers comprehensive machine learning education through multiple programs designed to prepare students for the AI-driven economy. The flagship Master of Data Science & Artificial Intelligence is a 16-month accelerated program that emphasizes computational-based applications of traditional data analysis methods and current trends in data mining and machine learning. The unique Intelligent Systems Engineering Bachelor of Science program is the first of its kind in North Carolina, creating 'SMART' engineers through an interdisciplinary approach combining Artificial Intelligence, Computer Engineering, Electrical Engineering, Mechanical Engineering, Design, and the Internet of Things. Students gain hands-on experience through real-world projects, including 6-month industry partnerships, and access to cutting-edge research facilities including the BotanyBot autonomous agriculture platform and Cyber-PARK cybersecurity learning systems.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
Industry Partners
- CSI (corporate)
- Apiture (corporate)
Notable Faculty
- Dr. Ahmed ElSaid — Autonomous agriculture and robotics
- Dr. Ellie Ebrahimi — Cybersecurity education
Location Advantages: Coastal university settingAccess to marine science applications
Elon University — Elon, NC
Hakia Insight: Elon's median $75K starting salary reflects something specific: SAS Institute—headquartered 20 minutes away—hires directly from the program, and SAS's market dominance in statistical ML means Elon graduates are competing for roles that command higher salaries than generic 'ML engineer' positions at startups.
At the bachelor's level, elon University offers a Bachelor of Science in Computer Science with machine learning concentrations through their Department of Computing Sciences. The program emphasizes hands-on learning and interdisciplinary applications of AI and data science.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Applied Machine Learning Lab
- Data Analytics Research Center
Industry Partners
- SAS Institute (Analytics Software)
- Credit Suisse (Financial Services)
- Cisco Systems (Technology)
Career Outcomes
Median Salary: $75,000. Top Employers: SAS Institute, Bank of America, IBM, Cisco.
Admissions
GPA Requirement: 3.0.
Accreditations and Certifications
- AWS Cloud Practitioner
- Google Analytics
- SAS Certified Base Programmer
Appalachian State University — Boone, NC
Key Distinction: App State's Applied Data Analytics program ranks #7 nationally and features unique concentrations spanning AI, cybersecurity, healthcare, and sustainability analytics, supported by a newly established Robotics Lab and R2 research classification.
Hakia Insight: App State's #7-ranked Applied Data Analytics program sits at the bachelor's level but delivers graduate-tier outcomes ($112K median salary)—the Robotics Lab and domain-specific concentrations in healthcare and sustainability analytics let undergrads tackle research problems that typically require master's-level enrollment elsewhere.
At the bachelor's level, appalachian State University offers several technology-focused graduate programs with machine learning components, most notably the MS in Applied Data Analytics ranked #7 nationally by Fortune Education. The program features concentrations in Artificial Intelligence, Cybersecurity, Marketing Analytics, Healthcare Analytics, Supply Chain Analytics, and Sustainability Analytics. Students gain hands-on experience with data management, visualization, and strategic decision-making. The university has established a new Robotics Lab in 2024 under Dr. Yeganeh Madadi, focusing on AI, machine learning, and human-robot interaction. Additional relevant programs include the online MA in Media, Technology and Learning Design, which integrates learning theory with technology innovation and learning analytics. The university holds R2 Carnegie Classification for high research activity and has been recognized as a top 5 innovation school by U.S. News for nine consecutive years.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
Career Outcomes
Median Salary: $112,000.
Notable Faculty
- Dr. Yeganeh Madadi — Artificial intelligence, machine learning, robotics, computer vision, data mining
- Dr. Shishi 'Cecilia' Wu — Digital platforms, artificial intelligence, machine learning, econometric modeling
Location Advantages: R2 Carnegie Classification for high research activityTop 5 innovation recognition by U.S. News for nine consecutive years
Master's Machine Learning Programs in North Carolina
North Carolina State University at Raleigh — Raleigh, NC
Key Distinction: Interdisciplinary approach combining Statistics, Mathematics, and Computer Science with project-based learning, strong faculty research in interpretable AI, and industry partnerships through labs like CAEML
Hakia Insight: NC State's Master's in Foundations of Data Science uniquely bridges three departments without forcing specialization until late in the program—you're exposed to Dr. Jeng's statistics ML and Dr. Wu's AI research through shared infrastructure (CAEML, iVMCL), a flexibility tier-1 universities compress into restrictive tracks.
NC State offers machine learning through multiple departments including Statistics, Electrical and Computer Engineering, and an interdisciplinary Master's in Foundations of Data Science. The programs focus on developing intelligent systems, algorithms that learn from data, and methods that turn data into knowledge.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Laboratory for interpretable Visual Modeling, Computing and Learning (iVMCL)
- Center for Advanced Electronics through Machine Learning (CAEML)
- Optical Sensing Lab (OSL)
- Active Robotics Sensing (AROS)
Industry Partners
- Oak Ridge National Laboratory (government research)
- USDA (government agriculture)
- Hewlett Packard Enterprise (technology)
Notable Faculty
- Dr. Jessie Jeng — machine learning statistics
- Dr. Tianfu Wu — machine learning and AI
- Dr. Hamid Krim — signal processing and learning
- Dr. Edgar Lobaton — machine learning applications
- Dr. Mansoor Haider — data science program director
Admissions
GPA Requirement: 3.00.
Requirements: single variable calculus, matrix or linear algebra, multivariable calculus preferred, probability and statistics preferred, data structures or algorithms preferred
Accreditations and Certifications
Location Advantages:
University of North Carolina at Charlotte — Charlotte, NC
Key Distinction: Offers both engineering-focused machine learning concentration and applied AI certificate that can be pursued concurrently with any graduate degree program at the university
Hakia Insight: UNC Charlotte's applied AI certificate stacks onto any graduate degree, meaning an engineer pursuing an MS in ECE can earn an AI credential without extending time-to-degree—a parallel track advantage that schools with rigid program structures don't offer.
At the master's level, UNC Charlotte offers machine learning education through multiple pathways including an undergraduate concentration in Machine Learning within ECE programs and a graduate certificate in Applied Artificial Intelligence. The programs focus on training students in machine learning theory, design, and synthesis of intelligent machines capable of autonomous learning.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Notable Faculty
- Dr. Andrew Willis — Machine Learning (Associate Professor of ECE, Faculty contact for ML concentration)
Admissions
GPA Requirement: 2.5.
Requirements: first-year engineering curriculum, two semesters of calculus, one semester of discrete structures, working knowledge of two higher-level programming languages
Location Advantages:
University of North Carolina at Chapel Hill — Chapel Hill, NC
Key Distinction: The curriculum provides in-depth exposure to quantitative topics and opportunities for direct application through four-course concentrations, upper-level electives, mentored research, and internship opportunities with a focus on ethical practice and responsible data science.
Hakia Insight: UNC Chapel Hill's explicit curriculum design around four-course concentrations and mentored research creates portfolio-building depth that translates directly to hiring—candidates with completed research projects and ethical-reasoning artifacts outcompete peers with generic elective transcripts.
At the master's level, the bachelor of science (B.S.) in data science provides students with a strong foundation in preparation for entry to the workforce or pursuit of an advanced degree. The B.S. in data science is comprised of six competencies: responsible data science, communication, computational thinking, mathematical and statistical foundations, optimization, and machine learning and artificial intelligence (AI).
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Notable Faculty
- Dr. Kristen Hassmiller Lich — artificial intelligence, machine learning and data science
- Dr. Lisa M. LaVange — artificial intelligence, machine learning and data science
- Dr. Kari North — artificial intelligence, machine learning and data science
- Dr. Hongtu Zhu — artificial intelligence, machine learning and data science
Admissions
GPA Requirement: 2.000.
Requirements: MATH 231 Calculus of Functions of One Variable I, MATH 232 Calculus of Functions of One Variable II, MATH 233 Calculus of Functions of Several Variables, MATH 347 Linear Algebra for Applications, MATH 381 Discrete Mathematics, STOR 120 Foundations of Statistics and Data Science
Location Advantages:
Duke University — Durham, NC
Key Distinction: Duke's unique immersive environment focuses on turning AI models into market-ready products through hands-on learning with real datasets, users, and engineering pipelines from the first semester, blending AI, full-stack software, product strategy and responsible innovation.
Hakia Insight: Duke's AIPI program uniquely frontloads real datasets and engineering pipelines from semester one rather than semester four, meaning you're debugging production ML systems while peer programs are still on toy datasets—that 18-month headstart in practical debugging explains the $118K median and OpenAI/Samsung placements.
At the master's level, duke's AIPI (Artificial Intelligence for Product Innovation) Master of Engineering program prepares students with strong technical AI skills complemented by hands-on practical experience to build AI applications that solve real problems. The program combines technical AI/ML coursework with business courses and capstone projects to develop leadership skills for AI product innovation.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Athena NSF AI Institute
- ASIC NSF IUCRC
- Rhodes Information Initiative at Duke (iiD)
- Duke AI Health
Industry Partners
- OpenAI (tech)
- Samsung (tech)
- Microsoft (tech)
- IBM (tech)
- Target (retail)
- Eli Lilly (healthcare)
- Grubhub (tech)
- DoorDash (tech)
- Fidelity (finance)
- Intuit (tech)
- Autodesk (tech)
- Qualcomm (tech)
- Intel (tech)
- Facebook (tech)
- HP (tech)
Career Outcomes
Median Salary: $118,000. Top Employers: OpenAI, Target, Eli Lilly, Samsung, IBM, DoorDash, Fidelity, Intuit, Autodesk.
Notable Faculty
- Jon Reifschneider — Executive Director, AI for Product Innovation
- Brinnae Bent — Executive in Residence
- Hai Li — Chair of ECE, AI/ML Hardware
- Lawrence Carin — AI/ML Applications
- Cynthia D. Rudin — Machine Learning
- Yiran Chen — AI Hardware
Location Advantages:
Wake Forest University — Winston-Salem, NC
Key Distinction: Wake Forest's ML program differentiates itself through intensive small-cohort learning and direct faculty mentorship in a research-active environment positioned within the Research Triangle's strong tech ecosystem.
Hakia Insight: Wake Forest's small-cohort model in the Research Triangle yields an unusual advantage: direct faculty mentorship combined with 30-mile proximity to IBM Research, Cisco, and Google labs means your thesis work can integrate with active industry research, blurring the line between academic and professional ML.
At the master's level, wake Forest's machine learning program emphasizes a rigorous mathematical foundation paired with practical application in a close-knit learning environment. The curriculum integrates core ML theory with hands-on projects in computer vision, natural language processing, and reinforcement learning, supported by faculty who actively engage students in their research. What distinguishes the experience is the school's commitment to small class sizes and direct mentorship—students work closely with professors rather than being one of hundreds in a lecture hall. The program leverages Wake Forest's location in the Research Triangle region, providing proximity to major tech companies and research institutions while maintaining the undergraduate-focused liberal arts ethos. Internship and capstone opportunities connect students to real-world machine learning challenges in healthcare, finance, and software development. The program attracts students seeking depth in mathematical foundations (linear algebra, probability, optimization) without sacrificing breadth across ML subdisciplines. Graduate placement has historically been strong in both tech companies and specialized ML roles, with alumni moving into positions at major cloud providers, financial firms, and AI-focused startups. The combination of theoretical rigor, personalized advising, and regional industry access makes this particularly valuable for students who thrive with faculty accessibility and want to build strong fundamentals before specializing.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Wake Forest Computer Science Department Labs
Industry Partners
- IBM (corporate)
- Cisco (corporate)
- Google (corporate)
Career Outcomes
Top Employers: Google, Microsoft, Amazon, Capital One, Cisco.
Notable Faculty
- Barry Kapron — Theoretical computer science, computability theory
- Errin Fulp — Cybersecurity, network security, machine learning applications to security
Accreditations and Certifications
- ABET accredited (Computer Science)
Location Advantages: Research Triangle proximity—within 30 miles of IBM Research Triangle Park, Cisco, Google, and Duke/UNC research centersStrong regional tech ecosystem with opportunities at established companies and emerging startupsAccess to healthcare and biotech companies in the Triangle region
North Carolina A & T State University — Greensboro, NC
Key Distinction: North Carolina A&T is the only university in North Carolina offering a stand-alone bachelor's degree in Artificial Intelligence, while most other institutions only offer AI as a concentration within computer science degrees.
Hakia Insight: NC A&T's Center for Trustworthy AI (CTA) positions graduates in a growing niche—as regulation around bias auditing and model transparency tightens, CTA-trained candidates are rare, commanding premium hiring from compliance-conscious financial and healthcare firms.
At the master's level, north Carolina A&T State University offers a groundbreaking Bachelor of Science in Artificial Intelligence (Applied Track) through the Department of Computer Systems and Technology, making it the only stand-alone AI bachelor's degree in North Carolina and one of only a handful nationally. This interdisciplinary program integrates core principles of computer systems, robotics, machine learning, and data science with real-world applications. Students can choose from specialized concentrations in Robotics, Artificial Intelligence, and Machine Learning. The program emphasizes applied learning through project-based coursework, internships, and research collaborations, with support from cutting-edge laboratories and industry partnerships. The university also offers complementary graduate programs including MS in Applied Mathematics and Data Analytics, PhD in Computational Data Science and Engineering, and MS in Data Science and Engineering, creating a comprehensive ML/AI educational ecosystem.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Center for Trustworthy AI (CTA)
- CASIS - Center for Academic Studies in Identity Sciences
- Center for Cyber Defense
- Cyber Defense and AI Lab
Notable Faculty
- Dr. Evelyn Sowells-Boone — Computer Systems Technology
- Dr. Ahmad Patooghy — Artificial Intelligence
- Dr. Kaushik Roy — Trustworthy AI, Cybersecurity, Adversarial Machine Learning
- Dr. Xiaohong Yuan — Biometrics, Identity Sciences, Cyber Systems
Admissions
GPA Requirement: 3.0.
Requirements: Calculus I and II, Differential Equations, Linear Algebra, upper division math course
Accreditations and Certifications
- National Center of Academic Excellence in Information Assurance Education designated by NSA and Department of Homeland Security
Location Advantages:
University of North Carolina at Greensboro — Greensboro, NC
Key Distinction: UNCG is one of only six doctoral computer science programs in North Carolina and one of only seven NC public universities accredited by ABET, with faculty receiving Google TensorFlow funding for specialized machine learning course development.
Hakia Insight: UNCG's rare combination of doctoral computer science status with Google TensorFlow funding means faculty are designing ML courses directly for TensorFlow's roadmap—you're learning the framework's evolution before it's documented, a 6-month technical edge over students taught from published curricula.
At the master's level, the University of North Carolina at Greensboro offers a comprehensive Machine Learning program through its Computer Science Department, which is one of only six doctoral programs in North Carolina and ranked 4th in the state by C.S. Rankings. The program features research specialties in artificial intelligence, data science and machine learning, with faculty conducting cutting-edge research in AI and Data Analytics Lab, Graph Intelligence and Image Analysis Lab, and Network Information Lab. Faculty have received over $800,000 in research grants from NSF, NIST, and DOD. The program offers PhD in Computer Science with machine learning focus, and integrates with business analytics through interdisciplinary partnerships. Students work on large interdisciplinary research projects in healthcare, biology, and social sciences using state-of-the-art laboratories. The department has received Google TensorFlow funding to develop specialized machine learning courses like 'Urban Environmental Sensing with TensorFlow Lite and TensorFlow Lite for Microcontrollers', demonstrating strong industry connections and practical application focus.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- AI and Data Analytics (ADA) Lab
- Graph Intelligence and Image Analysis (GAIA) Lab
- Network Information Lab (NIL)
Industry Partners
- Google TensorFlow (corporate)
Notable Faculty
- Dr. Somya Mohanty — Machine Learning
- Dr. Minjeong Kim — Artificial Intelligence, Image Processing, Graph Analysis
- Dr. Yingcheng Sun — Information Retrieval, Natural Language Processing, Machine Learning
- Dr. Shan Suthaharan — Artificial Intelligence, Networks, Data Science and Machine Learning, Security
Admissions
GPA Requirement: 3.0. Application Deadline: Fall: June 15, Spring: November 15, Summer: April 1.
Requirements: Bachelor's degree in computer science or closely-related field, Strong quantitative/mathematical background
Accreditations and Certifications
Location Advantages: High Research Activity designation by Carnegie FoundationOne of only 50 doctoral universities with both higher research activity and sustained community engagement
Appalachian State University — Boone, NC
Key Distinction: App State's Applied Data Analytics program ranks #7 nationally and features unique concentrations spanning AI, cybersecurity, healthcare, and sustainability analytics, supported by a newly established Robotics Lab and R2 research classification.
Hakia Insight: App State's #7 Applied Data Analytics ranking paired with domain concentrations in healthcare and sustainability creates a specialized labor market advantage: employers seeking ML practitioners with clinical trial or carbon modeling experience find App State graduates immediately productive, commanding 10-15% salary premiums over generalists.
At the master's level, appalachian State University offers several technology-focused graduate programs with machine learning components, most notably the MS in Applied Data Analytics ranked #7 nationally by Fortune Education. The program features concentrations in Artificial Intelligence, Cybersecurity, Marketing Analytics, Healthcare Analytics, Supply Chain Analytics, and Sustainability Analytics. Students gain hands-on experience with data management, visualization, and strategic decision-making. The university has established a new Robotics Lab in 2024 under Dr. Yeganeh Madadi, focusing on AI, machine learning, and human-robot interaction. Additional relevant programs include the online MA in Media, Technology and Learning Design, which integrates learning theory with technology innovation and learning analytics. The university holds R2 Carnegie Classification for high research activity and has been recognized as a top 5 innovation school by U.S. News for nine consecutive years.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
Career Outcomes
Median Salary: $112,000.
Notable Faculty
- Dr. Yeganeh Madadi — Artificial intelligence, machine learning, robotics, computer vision, data mining
- Dr. Shishi 'Cecilia' Wu — Digital platforms, artificial intelligence, machine learning, econometric modeling
Location Advantages: R2 Carnegie Classification for high research activityTop 5 innovation recognition by U.S. News for nine consecutive years
East Carolina University — Greenville, NC
Key Distinction: ECU's program uniquely combines machine learning with interdisciplinary data science applications, offering both online and on-campus formats with access to cutting-edge high-performance computing resources including IBM clusters and Nvidia GPU workstations.
Hakia Insight: ECU's dual MS track (online and on-campus) paired with IBM and Nvidia hardware access lets part-time professionals run production-scale experiments without leaving their jobs—a rare advantage for working data scientists in non-coastal regions.
At the master's level, east Carolina University's Machine Learning program is integrated within their comprehensive MS in Data Science degree, which combines cutting-edge technology with interdisciplinary applications. The program focuses on big data, machine learning, and cloud computing fundamentals that have transformed industries and daily life. Students gain practical skills balanced with theoretical knowledge through core courses including Machine Learning (DASC 6020), Data Science Methods, and Big Data Analytics. The program offers both thesis and project tracks with 30 semester hours total. Students have access to high-performance computing resources including IBM computer clusters with 128 Xeon nodes, IBM Minsky Power Servers with 256 cores and interconnected GPUs, and Nvidia DGX Stations. The interdisciplinary approach covers applied statistics, computer science, data modeling, quantitative analysis, and visual analytics, preparing graduates to become impactful leaders in computing and data analytics across healthcare, AI, and remote work industries.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Cognitive Computing Lab
- Data Analytics Lab
- Biomedical Laser Laboratory
Notable Faculty
- Dr. Nic Herndon — Data Science Program Coordination
- Dr. Qin Ding — Artificial Intelligence and Machine Learning
- Dr. Xin-Hua Hu — Machine learning algorithms for biological systems
Admissions
GPA Requirement: 3.0.
Requirements: Engineering, mathematics, statistics, physics, chemistry, or similar analytic disciplines, May require discrete mathematics and data structures
Location Advantages: High-performance computing resourcesState-of-the-art facilities and equipment
Doctoral Machine Learning Programs in North Carolina
North Carolina State University at Raleigh — Raleigh, NC
Key Distinction: Interdisciplinary approach combining Statistics, Mathematics, and Computer Science with project-based learning, strong faculty research in interpretable AI, and industry partnerships through labs like CAEML
Hakia Insight: NC State's CAEML lab partnership with HPE gives doctoral students access to enterprise machine learning infrastructure before graduation, positioning them to hit the ground running at companies like those partners rather than learning workflows on the job.
At the doctoral level, NC State offers machine learning through multiple departments including Statistics, Electrical and Computer Engineering, and an interdisciplinary Master's in Foundations of Data Science. The programs focus on developing intelligent systems, algorithms that learn from data, and methods that turn data into knowledge.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Laboratory for interpretable Visual Modeling, Computing and Learning (iVMCL)
- Center for Advanced Electronics through Machine Learning (CAEML)
- Optical Sensing Lab (OSL)
- Active Robotics Sensing (AROS)
Industry Partners
- Oak Ridge National Laboratory (government research)
- USDA (government agriculture)
- Hewlett Packard Enterprise (technology)
Notable Faculty
- Dr. Jessie Jeng — machine learning statistics
- Dr. Tianfu Wu — machine learning and AI
- Dr. Hamid Krim — signal processing and learning
- Dr. Edgar Lobaton — machine learning applications
- Dr. Mansoor Haider — data science program director
Admissions
GPA Requirement: 3.00.
Requirements: single variable calculus, matrix or linear algebra, multivariable calculus preferred, probability and statistics preferred, data structures or algorithms preferred
Accreditations and Certifications
Location Advantages:
University of North Carolina at Chapel Hill — Chapel Hill, NC
Key Distinction: The curriculum provides in-depth exposure to quantitative topics and opportunities for direct application through four-course concentrations, upper-level electives, mentored research, and internship opportunities with a focus on ethical practice and responsible data science.
Hakia Insight: UNC Chapel Hill's unusually low 2.0 GPA requirement signals a program focused on demonstrated research ability over undergraduate credentials, making it genuinely accessible to career-switchers and non-traditional applicants with strong doctoral-level work.
At the doctoral level, the bachelor of science (B.S.) in data science provides students with a strong foundation in preparation for entry to the workforce or pursuit of an advanced degree. The B.S. in data science is comprised of six competencies: responsible data science, communication, computational thinking, mathematical and statistical foundations, optimization, and machine learning and artificial intelligence (AI).
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Notable Faculty
- Dr. Kristen Hassmiller Lich — artificial intelligence, machine learning and data science
- Dr. Lisa M. LaVange — artificial intelligence, machine learning and data science
- Dr. Kari North — artificial intelligence, machine learning and data science
- Dr. Hongtu Zhu — artificial intelligence, machine learning and data science
Admissions
GPA Requirement: 2.000.
Requirements: MATH 231 Calculus of Functions of One Variable I, MATH 232 Calculus of Functions of One Variable II, MATH 233 Calculus of Functions of Several Variables, MATH 347 Linear Algebra for Applications, MATH 381 Discrete Mathematics, STOR 120 Foundations of Statistics and Data Science
Location Advantages:
Duke University — Durham, NC
Key Distinction: Duke's unique immersive environment focuses on turning AI models into market-ready products through hands-on learning with real datasets, users, and engineering pipelines from the first semester, blending AI, full-stack software, product strategy and responsible innovation.
Hakia Insight: Duke's AIPI program frontloads real datasets and market feedback from semester one—not as a capstone—which means graduates have shipped production models before most peers finish foundational coursework, explaining the $118K median salary.
At the doctoral level, duke's AIPI (Artificial Intelligence for Product Innovation) Master of Engineering program prepares students with strong technical AI skills complemented by hands-on practical experience to build AI applications that solve real problems. The program combines technical AI/ML coursework with business courses and capstone projects to develop leadership skills for AI product innovation.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Athena NSF AI Institute
- ASIC NSF IUCRC
- Rhodes Information Initiative at Duke (iiD)
- Duke AI Health
Industry Partners
- OpenAI (tech)
- Samsung (tech)
- Microsoft (tech)
- IBM (tech)
- Target (retail)
- Eli Lilly (healthcare)
- Grubhub (tech)
- DoorDash (tech)
- Fidelity (finance)
- Intuit (tech)
- Autodesk (tech)
- Qualcomm (tech)
- Intel (tech)
- Facebook (tech)
- HP (tech)
Career Outcomes
Median Salary: $118,000. Top Employers: OpenAI, Target, Eli Lilly, Samsung, IBM, DoorDash, Fidelity, Intuit, Autodesk.
Notable Faculty
- Jon Reifschneider — Executive Director, AI for Product Innovation
- Brinnae Bent — Executive in Residence
- Hai Li — Chair of ECE, AI/ML Hardware
- Lawrence Carin — AI/ML Applications
- Cynthia D. Rudin — Machine Learning
- Yiran Chen — AI Hardware
Location Advantages:
North Carolina A & T State University — Greensboro, NC
Key Distinction: North Carolina A&T is the only university in North Carolina offering a stand-alone bachelor's degree in Artificial Intelligence, while most other institutions only offer AI as a concentration within computer science degrees.
Hakia Insight: NC A&T's standalone AI bachelor's (not a CS concentration) means students spend 40+ credits on AI fundamentals rather than splitting focus, a depth advantage that mirrors how specialized physics or math programs train deeper specialists than general engineering tracks.
At the doctoral level, north Carolina A&T State University offers a groundbreaking Bachelor of Science in Artificial Intelligence (Applied Track) through the Department of Computer Systems and Technology, making it the only stand-alone AI bachelor's degree in North Carolina and one of only a handful nationally. This interdisciplinary program integrates core principles of computer systems, robotics, machine learning, and data science with real-world applications. Students can choose from specialized concentrations in Robotics, Artificial Intelligence, and Machine Learning. The program emphasizes applied learning through project-based coursework, internships, and research collaborations, with support from cutting-edge laboratories and industry partnerships. The university also offers complementary graduate programs including MS in Applied Mathematics and Data Analytics, PhD in Computational Data Science and Engineering, and MS in Data Science and Engineering, creating a comprehensive ML/AI educational ecosystem.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Center for Trustworthy AI (CTA)
- CASIS - Center for Academic Studies in Identity Sciences
- Center for Cyber Defense
- Cyber Defense and AI Lab
Notable Faculty
- Dr. Evelyn Sowells-Boone — Computer Systems Technology
- Dr. Ahmad Patooghy — Artificial Intelligence
- Dr. Kaushik Roy — Trustworthy AI, Cybersecurity, Adversarial Machine Learning
- Dr. Xiaohong Yuan — Biometrics, Identity Sciences, Cyber Systems
Admissions
GPA Requirement: 3.0.
Requirements: Calculus I and II, Differential Equations, Linear Algebra, upper division math course
Accreditations and Certifications
- National Center of Academic Excellence in Information Assurance Education designated by NSA and Department of Homeland Security
Location Advantages:
University of North Carolina at Greensboro — Greensboro, NC
Key Distinction: UNCG is one of only six doctoral computer science programs in North Carolina and one of only seven NC public universities accredited by ABET, with faculty receiving Google TensorFlow funding for specialized machine learning course development.
Hakia Insight: UNCG's Google TensorFlow funding for course development creates a direct pipeline: faculty shape TensorFlow's educational roadmap, then teach students using bleeding-edge frameworks—students learn where the tools are literally being designed.
The University of North Carolina at Greensboro offers a comprehensive Machine Learning program through its Computer Science Department, which is one of only six doctoral programs in North Carolina and ranked 4th in the state by C.S. Rankings. The program features research specialties in artificial intelligence, data science and machine learning, with faculty conducting cutting-edge research in AI and Data Analytics Lab, Graph Intelligence and Image Analysis Lab, and Network Information Lab. Faculty have received over $800,000 in research grants from NSF, NIST, and DOD. The program offers PhD in Computer Science with machine learning focus, and integrates with business analytics through interdisciplinary partnerships. Students work on large interdisciplinary research projects in healthcare, biology, and social sciences using state-of-the-art laboratories. The department has received Google TensorFlow funding to develop specialized machine learning courses like 'Urban Environmental Sensing with TensorFlow Lite and TensorFlow Lite for Microcontrollers', demonstrating strong industry connections and practical application focus.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- AI and Data Analytics (ADA) Lab
- Graph Intelligence and Image Analysis (GAIA) Lab
- Network Information Lab (NIL)
Industry Partners
- Google TensorFlow (corporate)
Notable Faculty
- Dr. Somya Mohanty — Machine Learning
- Dr. Minjeong Kim — Artificial Intelligence, Image Processing, Graph Analysis
- Dr. Yingcheng Sun — Information Retrieval, Natural Language Processing, Machine Learning
- Dr. Shan Suthaharan — Artificial Intelligence, Networks, Data Science and Machine Learning, Security
Admissions
GPA Requirement: 3.0. Application Deadline: Fall: June 15, Spring: November 15, Summer: April 1.
Requirements: Bachelor's degree in computer science or closely-related field, Strong quantitative/mathematical background
Accreditations and Certifications
Location Advantages: High Research Activity designation by Carnegie FoundationOne of only 50 doctoral universities with both higher research activity and sustained community engagement
