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The MPS Applied AI program is forward-thinking, aiming to prepare students proactively and thoughtfully for the evolving technology landscape and its challenges. The curriculum focuses on building and implementing AI and machine learning (ML) technologies, with specializations in conversational AI, machine learning for cybersecurity, 3D imaging, and a range of electives. This comprehensive approach ensures that students are equipped with the skills and knowledge needed to stay ahead in the rapidly changing field of AI. The curricula framework adopts a multidisciplinary approach to problem-solving by combining computer science and analytical skills with functional government and industry expertise, creativity, and leadership.

Concentrations:

• Conversational AI and Chatbots: Blending linguistics, tech, and design, they enhance user experiences and business operations. The field offers vast research, especially in Natural Language Processing, and emphasizes ethical AI practices. As industries adopt AI, expertise here opens diverse career avenues, from global enterprises to local businesses.
• Machine Learning for Cybersecurity: Machine Learning (ML) enhances cybersecurity by detecting threats, automating responses, and scaling operations. ML spots sophisticated threats in vast datasets, streamlines responses, and predicts future risks. Its adaptive learning surpasses traditional systems, reduces false positives, and can be customized for organizations. As cyber threats evolve, ML’s role in defense and job relevance grows, offering novel research opportunities and countering advanced threats. ML is vital for the future of cybersecurity.
• AI for 3D Imaging: Offers improved accuracy, faster workflows, and clarity in fields such as healthcare and entertainment. It aids in data augmentation, real-time analysis, image segmentation, noise reduction, and cost efficiency. Its application in design predicts real-world impacts, and as industries adopt it, expertise becomes vital, driving innovations in gaming, film, and Virtual Reality.

Program Objectives
By the end of the program, students will be able to:

• Apply a comprehensive foundation in ML and AI concepts, methodologies, and applications for aspiring developers, engineers, and data scientists with minimal prior technical experience.
• Employ instrumental data analysis methods and modern artificial intelligence (AI) analytical techniques as applied in public and private sector settings.
• Investigate and select data, analytics, and AI technologies to address real-world organizational questions or problems.
• Solve an organizational problem by integrating the principles, tools, and methods of AI and machine learning (ML) while making informed decisions about the design and deployment of systems in human environments and related workflows.
• Evaluate advanced data management technologies for suitability in different application contexts and factors influencing successful adoption.
• Communicate complex quantitative information to different audiences using exploratory data visualization, dashboard design, scorecard design, and spatial data representation.
• Identify key management and ethical issues organizations face throughout the complete data lifecycle.
• Integrate the theory and practices of human-computer interaction and usability to analyze and design solutions.
• Apply strategic analysis, problem-solving, decision-making, effective communication, and leadership skills to implement ML and AI solutions in real-world scenarios.