Best Machine Learning Programs in Florida 2025

Florida offers 20 bachelor's-level machine learning programs. The top schools for undergraduate study are University of Miami, Florida Polytechnic University, University of North Florida. These programs prepare students for entry-level positions paying approximately $68,474 in the Florida market.

A bachelor's in machine learning typically requires 120-128 credit hours and takes 4 years to complete. For national rankings, see our Best Machine Learning Bachelor's Programs guide.

For graduate study, Florida offers 12 master's-level machine learning programs. Leading institutions include University of Miami, University of South Florida, The University of Tampa. A master's degree can boost earning potential by 15-25%, with senior roles in Florida reaching $127,166 or more.

For budget-conscious students, the most affordable machine learning programs in Florida are at Florida Atlantic University ($2,522/year), Florida Polytechnic University ($3,152/year), University of West Florida ($3,735/year). These programs offer strong ROI given Florida's competitive tech salaries.

At Florida Atlantic University, a 4-year degree costs approximately $10,088 in tuition alone. With entry-level salaries around $68,474, graduates can typically recoup their investment within 0.3 years.

Florida's machine learning job market experienced unprecedented growth in 2024, with tech employment increasing by 23% statewide. The state now hosts over 12,500 machine learning engineering positions, concentrated primarily in Miami-Dade, Orange, and Hillsborough counties. Major employers like Magic Leap, Chewy, and Ultimate Software have established significant ML operations in Florida, while traditional industries like aerospace and healthcare increasingly adopt AI solutions.

Entry-level machine learning engineers in Florida earn an average starting salary of $98,000 annually, with experienced professionals commanding $165,000 or more. Miami ranks as the 8th highest-paying metro for ML roles nationally, while Tampa and Orlando offer competitive packages with lower living costs. The state's lack of income tax provides additional financial advantages for tech professionals.

Industry demand spans multiple sectors including fintech, healthcare technology, aerospace, and gaming. Companies like Modernizing Medicine and MDLIVE drive healthcare AI innovation, while established aerospace contractors Boeing and Lockheed Martin seek ML talent for defense applications. The gaming industry, centered around Orlando's EA Tiburon and other studios, creates additional demand for computer vision and recommendation system expertise.

• Miami-Dade: 3,200+ ML positions, average salary $128,000
• Orange County (Orlando): 2,800+ positions, average salary $115,000
• Hillsborough County (Tampa): 2,100+ positions, average salary $118,000
• Broward County: 1,900+ positions, average salary $122,000
• Palm Beach County: 1,200+ positions, average salary $119,000

Florida's machine learning education landscape divides clearly between well-funded public research universities and specialized private institutions. Public universities like University of Florida and Florida State offer comprehensive programs at significantly lower costs, with in-state tuition averaging $21,500 annually. These institutions benefit from substantial state research funding and established industry partnerships.

Private institutions like Florida Institute of Technology and University of Miami provide more personalized attention with smaller class sizes averaging 18 students versus 35 at public universities. Private programs often feature cutting-edge facilities and closer industry connections, but at nearly double the cost. The ROI calculation becomes complex when comparing program outcomes, as private school graduates may command slightly higher starting salaries but carry significantly more debt.

Research opportunities vary considerably between sectors. Public universities typically offer more graduate research assistantships and federal funding opportunities, while private institutions may provide more direct industry collaboration projects. Students interested in academic research careers should consider public programs, while those targeting immediate industry employment might prefer private institutions' industry-focused curricula.

Most Florida machine learning programs require strong mathematical foundations, with calculus through multivariable calculus, linear algebra, and statistics prerequisites universally expected. Computer science background including data structures, algorithms, and programming proficiency in Python or R are standard requirements. Top-tier programs like University of Florida typically require minimum 3.7 GPA for competitive admission, while mid-tier programs accept students with 3.3+ GPA.

Standardized test requirements vary significantly between institutions. Public universities generally require GRE scores for graduate programs, with competitive programs expecting quantitative scores above the 80th percentile. Private institutions may waive GRE requirements for applicants with strong professional experience or relevant undergraduate coursework. International students should plan for additional requirements including TOEFL scores above 90 and demonstration of English proficiency.

• Bachelor's degree in computer science, mathematics, engineering, or related field
• Minimum 3.3 GPA for most programs, 3.7+ for top-tier institutions
• Calculus I-III, linear algebra, and statistics coursework
• Programming experience in Python, R, or similar languages
• GRE scores (varies by institution): typically 160+ quantitative
• Letters of recommendation from academic or professional contacts
• Statement of purpose highlighting ML career goals and relevant experience

Florida machine learning curricula emphasize practical application alongside theoretical foundations. Core coursework universally includes supervised and unsupervised learning, deep learning architectures, and statistical inference methods. Advanced programs like University of Florida's ML track require specialized courses in computer vision, natural language processing, and reinforcement learning, providing comprehensive coverage of modern ML techniques.

Hands-on experience varies significantly between programs. Florida Institute of Technology requires a year-long capstone project with industry sponsors, while University of Miami emphasizes interdisciplinary applications in healthcare and business analytics. Students should evaluate program curricula against their career interests, as specializations in computer vision, NLP, or robotics require different foundational courses.

Programming language emphasis differs across institutions. Most programs center on Python with TensorFlow and PyTorch frameworks, though some include R for statistical analysis or MATLAB for signal processing applications. Advanced programs incorporate cloud computing platforms like AWS and Google Cloud, essential skills for modern ML deployment. Database management and big data processing using Spark and Hadoop round out the technical curriculum.

University of Florida leads Florida institutions in machine learning research output, with faculty publishing over 180 peer-reviewed papers annually in top-tier venues like NeurIPS and ICML. The university's machine learning lab focuses on computer vision applications for agriculture and medical imaging, leveraging Florida's unique agricultural and healthcare industries. Research funding exceeds $2.3 million annually from NSF, NIH, and industry partners.

Florida Institute of Technology specializes in applied research with strong industry connections. Faculty collaborate with local aerospace companies on ML applications for autonomous systems and satellite imagery analysis. The proximity to Kennedy Space Center creates unique research opportunities in space technology applications. Students regularly present findings at major conferences and contribute to patent applications.

Undergraduate research opportunities exist at most institutions, though competitive admission is required. Research experience significantly strengthens graduate school applications and provides valuable networking opportunities with faculty and industry professionals. Students interested in PhD programs should prioritize institutions with active research labs aligned with their interests.

Florida residents benefit from significant state funding advantages, with Bright Futures scholarships covering up to 100% of tuition costs for high-achieving students. The Florida Academic Scholars award provides $3,340 annually, while Florida Medallion Scholars receive $2,340 per year. These awards apply to machine learning programs at all state universities, making public education extremely affordable for qualified residents.

Graduate assistantships represent the most valuable funding source for ML students, with research assistantships at UF providing full tuition waivers plus $28,000 annual stipends. Teaching assistantships offer similar benefits while providing valuable pedagogical experience. Private institutions typically offer merit-based scholarships ranging from $10,000 to $25,000 annually, though full funding remains competitive.

Industry-sponsored scholarships target underrepresented groups in technology fields. Programs like the Google AI scholarship and Microsoft AI for Good initiative provide $5,000-$15,000 awards specifically for machine learning students. Companies like Magic Leap and Ultimate Software also offer internship programs with potential for full-time employment upon graduation.

• Bright Futures Academic Scholars: Up to $3,340/year (Florida residents)
• Graduate Research Assistantships: Full tuition + $25,000-$30,000 stipend
• NSF Graduate Research Fellowship: $37,000 stipend + tuition coverage
• Industry scholarships: $5,000-$15,000 from tech companies
• Diversity in AI scholarships: Various amounts for underrepresented groups
• Work-study programs: $8,000-$12,000 annually for qualified students