This course introduces students to the principles, methodologies, and tools used in modern engineering product design. Students learn the complete product development process, from opportunity identification and customer needs analysis through concept generation, prototyping, testing, manufacturing considerations, and product launch.
The course emphasizes human-centered design, design thinking, engineering creativity, rapid prototyping, digital modeling, and sustainable product development while integrating Artificial Intelligence (AI) tools to support ideation, design optimization, documentation, and engineering decision-making.
Students work on authentic engineering challenges to design innovative products using industry-standard methodologies and collaborative design processes.
- Teacher: Rodolfo Capdevilla
- Teacher: Luis Perez Macias
This course focuses on how modern Large Language Models (LLMs) work and how to build with them, moving from the mechanics of attention and the Transformer architecture to running, customizing, and deploying your own models. Students progress from understanding tokenization, embeddings, and self-attention to applying prompting, retrieval-augmented generation (RAG), and fine-tuning, culminating in training and serving a Small Language Model (SLM) that runs locally on Atlantis University hardware. The course emphasizes hands-on experimentation, real-world use cases, and the integration of modern AI tools such as Claude Code, OpenAI Codex, GitHub Copilot, and the Hugging Face ecosystem. Students will work across two learning tracks (low-code and high-code), allowing them to either focus on conceptual understanding and applied AI tools or develop advanced programming and model implementation skills.
By the end of the course, students will be able to build end-to-end LLM and SLM solutions and understand how modern language-model systems are designed, customized, and deployed in practice.
- Teacher: Ivan Suarez
This course introduces students to the fundamental principles of computer programming and computational thinking through the Python programming language. Emphasis is placed on problem-solving, algorithm development, program design, and the implementation of programming constructs used in modern software applications. Students explore data types, control structures, functions, files, and essential data structures while developing logical reasoning and analytical skills.
Through hands-on programming activities and real-world applications, students gain practical experience in designing, implementing, testing, and documenting programs. The course promotes structured programming practices and prepares students for more advanced studies in software development, data science, and information technology.
- Teacher: William Rodriguez
This course provides graduate students with advanced knowledge and practical skills required to plan, execute, monitor, and close information technology projects in complex organizational environments. Emphasis is placed on project governance, stakeholder management, agile and predictive methodologies, risk analysis, resource allocation, quality assurance, and digital transformation initiatives.
Students develop competencies in project planning, scheduling, budgeting, performance measurement, and organizational change management through authentic learning experiences supported by project management software, artificial intelligence tools, and industry-based simulations. The course integrates PMBOK® principles and contemporary project management practices to prepare students to lead technology-driven projects and support strategic organizational objectives.
- Teacher: Slavica Mitreva (FACULTY)
Managing Cloud Technology Identities is an 8-week course designed to introduce students to the fundamentals of identity management in cloud environments, with a primary focus on Microsoft Entra ID (formerly Azure Active Directory). Through practical, hands-on assignments, students will learn essential concepts, tools, and techniques for managing identities, users, groups, and access controls in Azure and understand the broader context of identity management in cloud technology.
- Teacher: William Rodriguez
MET 520 is a master's-level, hands-on cloud computing and data analytics course delivered across 8 progressive weeks. Students develop the skills required to architect, deploy, secure, monitor, and operate enterprise cloud solutions on AWS, Microsoft Azure, and Google Cloud building working proof-of-concepts on real cloud platforms throughout the course rather than through case studies alone.
Each week is anchored to a real-world business scenario in a different industry vertical: healthcare (Coral Bay Medical Center, Atlas Health Group), logistics (Magnolia Logistics), financial services (Quantum Financial Services), manufacturing (BlueRidge Manufacturing), media (StreamWave Media), retail (Helix Retail), and a student-selected vertical for the final capstone (Atlantis Technologies). The scenario format ensures students develop not only technical competence but also the strategic and consultative thinking expected at the master's level.
A defining feature of MET 520 is the explicit integration of generative AI throughout the cloud architecture lifecycle. Students apply AI tools (Claude, ChatGPT, Microsoft Copilot, Gemini) every week to architecture design, threat modeling, capacity modeling, infrastructure-as-code generation, SQL authoring, and executive communication and they critically evaluate every AI output for accuracy, bias, and completeness. The course produces graduate who can lead cloud initiatives in their organizations and who can integrate AI into their professional practice transparently and effectively.
- Teacher: Slavica Mitreva (FACULTY)