Pending WSCUC Approval

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The AI and Machine Learning for Science and Technology track is designed for:

  • Science and Technology Professionals: Working professionals currently in science and technology roles who wish to implement AI/ML technology or increase their existing technical skills in this field

  • Early- to Mid-Career Technology Professionals: Individuals looking to transition into leadership positions within their companies by combining technical AI upskilling with business and management training

  • Individuals with Strong Quantitative Backgrounds: Those who have a solid record of academic achievement in subjects such as computer programming, mathematics, and science

  • Recent Graduates with Leadership Potential: Graduates who may not yet be in the workforce but have demonstrated an aptitude for entrepreneurship or leadership potential, and can satisfy a minimum non-academic employment requirement (such as an internship)


The AI and Machine Learning for Science and Technology track is designed to prepare students for the following specialized leadership and technical careers:

  • Corporate Leadership in Technology: Transitioning early- to mid-career technology professionals into senior leadership and management roles within their organizations

  • Scientific Research and Development (R&D) Specialist: Applying foundational and advanced AI methods to solve complex research problems across various scientific and engineering disciplines

  • Technical Management of AI Teams: Leading technology, innovation, or entrepreneurial teams specifically tasked with developing AI-driven products or solving high-level technical challenges

  • Responsible AI and Ethics Lead: Managing the societal, legal, and philosophical implications of AI technologies, with a focus on accountability, fairness, and transparency

  • Scientific Data Scientist: Handling the generation, statistical analysis, and interpretation of large-scale data sets specifically within scientific research and technological innovation sectors

  • AI-Human Collaboration Manager: Designing work processes that optimally combine human intelligence with intelligent technologies and leading teams in AI-rich environments

  • Technology Entrepreneur: Equipping students with the business model development, product ideation, and capital acquisition skills necessary to launch or lead AI-focused startups


To qualify for the AI and Machine Learning for Science and Technology track, applicants should possess a strong quantitative foundation and relevant professional or academic experience. The specific requirements are categorized as follows:

  • STEM-Related Degree: The program is primarily intended for students with backgrounds in STEM-related fields

  • Quantitative Competence: If an applicant does not have a STEM degree, they must demonstrate a solid record of academic achievement in quantitative coursework, including:

    • Mathematics

    • Science subjects

    • Computer programming

  • Core Concepts: For specific courses within the track foundational knowledge in basic matrix computations and probability and statistics at the undergraduate level is recommended

  • Programming Proficiency: Many core courses require a basic working knowledge and the ability to code in at least one programming language (preferably Python), which may be achieved through traditional study or "vibe coding"