Artificial Intelligence and Machine Learning

Sha’Kia M. Riggins, MSIT is a nationally recognized leader in artificial intelligence education, applied machine learning, and ethical AI implementation. She currently serves as the Dean of Information Technology at Florida State College at Jacksonville (FSCJ), where she leads strategic initiatives that position the institution at the forefront of workforce-aligned AI education. A U.S. Navy veteran and seasoned technologist, Riggins brings more than three decades of experience spanning industry, entrepreneurship, and academia. She is the CEO of Data B.I.T.S., LLC and has been instrumental in establishing FSCJ as an East Coast AI Center of Excellence, developing innovative degree programs, technical certificates, and industry partnerships that expand access to AI education. Riggins is the author of Artificial Intelligence and Machine Learning: Concepts, Applications, and Ethical Considerations (1st Edition), a foundational text that bridges theory, real-world applications, and responsible AI practices. Her work emphasizes ethical frameworks, workforce readiness, and inclusive innovation, and she is frequently sought after by publishers and industry to shape next-generation AI curriculum and learning tools. She serves as a Lead Facilitator for Intel’s Digital Readiness and AI Workforce Programs, helping train educators nationwide, and is an active member of the National Applied AI Consortium for Educators, IEEE, and multiple AI advisory boards. Her collaborations with global industry partners have influenced applied AI education both nationally and internationally. A passionate advocate for mentorship and equity in technology, Riggins is committed to preparing the next generation of AI leaders while ensuring that innovation is guided by ethics, accountability, and social impact. Sha’Kia M. Riggins, MSIT is a nationally recognized leader in artificial intelligence education, applied machine learning, and ethical AI implementation. She currently serves as the Dean of Information Technology at Florida State College at Jacksonville (FSCJ), where she leads strategic initiatives that position the institution at the forefront of workforce-aligned AI education. A U.S. Navy veteran and seasoned technologist, Riggins brings more than three decades of experience spanning industry, entrepreneurship, and academia. She is the CEO of Data B.I.T.S., LLC and has been instrumental in establishing FSCJ as an East Coast AI Center of Excellence, developing innovative degree programs, technical certificates, and industry partnerships that expand access to AI education. Riggins is the author of Artificial Intelligence and Machine Learning: Concepts, Applications, and Ethical Considerations (1st Edition), a foundational text that bridges theory, real-world applications, and responsible AI practices. Her work emphasizes ethical frameworks, workforce readiness, and inclusive innovation, and she is frequently sought after by publishers and industry to shape next-generation AI curriculum and learning tools. She serves as a Lead Facilitator for Intel’s Digital Readiness and AI Workforce Programs, helping train educators nationwide, and is an active member of the National Applied AI Consortium for Educators, IEEE, and multiple AI advisory boards. Her collaborations with global industry partners have influenced applied AI education both nationally and internationally. A passionate advocate for mentorship and equity in technology, Riggins is committed to preparing the next generation of AI leaders while ensuring that innovation is guided by ethics, accountability, and social impact.

• Introduction to Artificial IntelligenceEthical Impact of AIIntroduction to Machine LearningProgramming for Machine Learning ApplicationsData for Machine LearningUnderstanding Math Fundamentals for Machine Learning ApplicationsComputer VisionNatural Language ProcessingReinforcement LearningDeep Learning: A Subset of AI and a Key Technology Driving Modern AI SystemsNeural Networks: A Foundational Concept within AI and Central to Machine LearningFuture of AI & Machine Learning