FGCU AI Summer Academy

"AI Literacy" (Workshop)

9:00am-12:00pm EDT
May 4

Instructor: Dr. Leandro de Castro
Location: TBA
Goal:
Equip learners with enough understanding to confidently use and critically evaluate AI tools.

Topics:

• A Brief History of AI
• What is AI and Its Many Branches
• How Machines Learn
• Generative AI & LLMs
• Fundamentals of Prompt Engineering
• Context Engineering
• Foundational Models and Tools
• Sample Use Cases

"AI Leadership and Strategy" (Workshop)

1:00pm-4:00pm EDT
May 4

Instructor:  Maka Tsulukidze 
Location: TBA
Goal: 
Participants will examine practical frameworks for understanding and governing artificial intelligence at the institutional level. By the end of the session, learners will be better equipped to evaluate AI initiatives, identify risks and responsibilities, and articulate a clear, context-specific approach to AI strategy aligned with organizational values, workforce realities, and public trust.

Topics:

• AI at the Institutional Level: Examining how AI functions within organizations beyond individual tools, including its role in shaping decision-making, work practices, and infrastructure.
• Evaluating AI Initiatives and Use Cases: Practical frameworks for assessing proposed AI applications, including questions of value, feasibility, and alignment with institutional goals.
• Risk, Responsibility, and Accountability: Identifying ethical, legal, and reputational risks associated with AI use, and clarifying where responsibility should reside when AI influences decisions.
• Workforce and Organizational Implications: Exploring how AI affects roles, workload, and professional judgment for faculty, staff, and clinical teams.
• Light-Touch Governance and Guardrails: Approaches to oversight, transparency, and decision rights that support responsible AI use without excessive bureaucracy.
• Strategy Translation: Guided reflection to help participants articulate a preliminary, context-specific approach to AI strategy or governance for their unit or organization.

"Designing with AI, Not Around It: Effective Pedagogical Strategies for AI Integration in Higher Education" (Workshop)

9:00am-12:00pm EDT
May 5

Instructor: Ahmed Elshall
Location: TBA
Goal:
Equip faculty with a framework and practical strategies to intentionally integrate generative AI into course design and assessment while preserving academic rigor, learner agency, and foundational knowledge.

Topics:

• Why reactive AI policies fail: evidence from higher education
• The FACT–A3 framework for AI-integrated course and assessment design
• Pedagogical strategies for aligning AI use with learning goals
• Assignment design: no-AI, AI-resistant, structured AI, and open AI use
• Designing hybrid assessments that balance AI support and rigor
• Instructor roles in AI-enabled learning: mentoring and metacognitive modeling
• Hands-on redesign of participant assignments using the framework 

"Beyond the Hype: Demystifying AI for Educators and Professionals" (Webinar)

3:00pm-5:00pm EDT
May 5

Instructor: Rachel Cooke & Heidi Cramer
Location: TBA
Goal:
This session equips educators and researchers with a clear, jargon-free understanding of what AI actually is, how it works, and where it's headed—cutting through misinformation and hype to provide practical frameworks for responsible, effective AI integration in teaching, research, and academic workflows. Participants will leave with actionable strategies and renewed confidence to engage with AI tools on their own terms.

Topics:

• What AI really means—and what it doesn't: An accessible, plain-language introduction to core AI concepts, dispelling common myths and misconceptions about generative AI, machine learning, and automation
• How today's AI tools actually work: Understanding the technology behind ChatGPT, image generators, and research assistants without requiring a computer science background
• AI in the classroom right now: Exploring current applications—from smart classroom assistants to adaptive learning platforms—and what's working (and what isn't) in higher education
• Time-saving AI tools for educators and researchers: Practical demonstrations of AI applications for lesson planning, grading assistance, literature reviews, data analysis, and administrative workflows.
• Navigating academic integrity in the AI era: Frameworks for developing clear AI policies, having productive conversations with students, and rethinking assessment in a world where AI is ubiquitous
• What the next year of AI will bring: A forward look at emerging capabilities, Fgcu regulatory developments, and how educators can prepare for rapid technological change
• Ethical considerations and responsible adoption: Addressing bias, privacy, accessibility, and the human elements that AI cannot replace—ensuring technology empowers rather than diminishes teaching and learning

"Introduction to Programming with AI" (Training)

10:00am-12:00pm EDT
May 5 - May 8

Instructor: Vinod Ahuja
Location: TBA
Goal:
This hands-on training introduces the use of AI tools in coding—from auto-completion and code generation to debugging support. Participants will work with platforms like GitHub Copilot and AI-based IDE features to streamline software development.

Topics:

• Use AI tools for code completion and refactoring
• Boost productivity in software development with AI assistance
• Understand how AI integrates with modern IDEs
• Reflect on the ethical implications of AI-generated code

"Machine Learning with AI" (Training)

1:00pm-3:00pm EDT
May 5 - May 8

Instructor: Vinod Ahuja
Location: TBA
Goal: 
In this advanced training, participants will learn to design and implement machine learning solutions using modern AI platforms. They will go from data preprocessing to model evaluation and deployment through a guided project.

Topics:

• Design end-to-end ML pipelines
• Implement supervised learning models
• Evaluate and tune model performance
• Deploy machine learning solutions using standard tools

"Human-Centered AI for South Florida Water" (Webinar)

9:00am-11:00am EDT
May 6

Instructor: Ahmed Elshall
Location: TBA
Goals:
Provide participants with a high-level understanding of how AI can support insight and decision-making in South Florida water systems, while emphasizing responsible use, and limitations.

Topics:

• South Florida water systems as human–natural–data systems
• Where AI fits in environmental and water research and where it does not
• Using machine learning for pattern detection and early-warning insights
• Uncertainty, bias, and model limitations in AI-enabled water applications
• Large language models as interfaces to complex environmental data
• Human-centered AI for environmental education and decision support 

"Vibe Code Your Vision: Build a Functional Design Mini-App" (Workshop)

3:00pm-6:00pm EDT
May 6

Instructor: Brian Zajac
Location: TBA
Goals:
Build AI-powered mini-apps using Google AI Studio to turn your ideas into functional prototypes without traditional programming.

Topics:

• Improving prompt context & engineering for professional-grade image generation
• Applying UX and "vibe coding" principles for rapid, iterative app development
• Navigating the Google AI Studio "Build" feature and customizing application templates
• Learn the difference between prototyping and Go-to-market (GTM) web applications for the masses
• Choosing between the 50,000+ Replicate models to access advanced, specialized AI models

"Publishers and AI" (Webinar)

9:00am-11:00am EDT
May 7

Instructor: Em Farmer
Location: TBA
Goals:
After this session, participants will better understand major academic publishers’ policies on AI use and be able to apply best practices for transparent, ethical, and compliant scholarly publishing. 

Topics:

• Types of AI use in research
• AI and research integrity
• AI and peer review
• Copyright and AI
• Publisher statements and polices on AI
• AI in grant writing

"Getting your students reading again with the Alethea AI reading coach" (Webinar)

9:00am-11:00am EDT
May 8

Instructor: Tracy Elliott
Location: TBA
Goals:
Participants will be able to see how to incorporate the Alethea Reading Coach (GenAI) into their courses in a way that increases student comprehension of required readings or complex texts such as empirical research articles, preparing them for course discussions, and assessing their learning.

Topics:

• The GenAI chat that helps learn
• Increasing learning and engagement in any class
• How FGCU faculty are using Alethea
• How to get started using Alethea
• How Alethea integrates easily in Canvas

"Can You Trust AI? Practical Ways to Verify, Fact-Check, and Use GenAI Safely" (Workshop)

9:00am-12:00pm EDT
May 11

Instructor: Md Baharul Islam
Location: TBA
Goals:
Participants will learn practical, repeatable techniques to verify AI outputs, fact-check claims, validate citations and judge when AI content is trustworthy enough to use. 

Topics:

• Why AI makes mistakes (common failure modes)
• Claim, evidence and confidence verification workflow
• Fact checking with multiple reliable sources
• Validating citations, quotes, and links
• Checking numbers, calculations, and data claims
• Prompts that force transparency
• Hands-on practice with take-home checklist 

"AI Cofounder: Designing New Businesses with AI " (Training)

2:00-6:00pm EDT
May 11 - May 15

Instructor: Dr. Leandro de Castro
Location: TBA
Goals:
Enable participants to conceptualize, design, and prototype new business models and ventures using AI as a strategic cofounder, supporting ideation, validation, operations, and growth planning.

Topics:

• The GenAI Toolkit
  
• AI Literacy
• Stratgic Positioning
• Customer Development
• Design Thinking and Ideation
• Lean Startup
• Business Model Canvas
• Legal and Ethics for Startups
• Funding and Investment Readiness
• Pitching Your Startup

"Data Analysis with AI" (Training)

1:00pm-3:00pm EDT
May 11 - May 15

Instructor: Dr. Leandro de Castro
Location: TBA
Goals:
This training introduces participants to core concepts and practical techniques in data analysis enhanced by artificial intelligence. Through a blend of theory and hands-on exercises, participants will explore the basics of data analysis and how AI methods can uncover patterns, automate insights, and drive decision-making from data. The training emphasizes the use of AI tools for real-world applications in various fields.

Learning Outcomes:

• Understand the foundations of data analysis and its integration with AI
• Evaluate and visualize data insights
• Use data to inform decisions in various settings
• Apply AI tools to analyze structured datasets

"AI in Systematic Reviews and Evidence Synthesis" (Webinar)

9:00am-11:00am EDT
May 12

Instructor: Kimberly Reycraft
Location: TBA
Goals:
Gain a practical understanding of how AI is being applied across the stages of the systematic review process, along with its benefits, challenges and limitations.

Topics:

• Identify key systematic review stages where AI enhances efficiency and accuracy.
• Describe and differentiate AI tools supporting automation in evidence synthesis and their applications.
• Analyze AI's impact on workflow efficiency, rigor, transparency, and reproducibility in systematic reviews.
• Evaluate benefits, challenges, limitations, and ethical considerations of AI in evidence synthesis with justification.
• Apply standards and best practices to design and implement an AI-integrated systematic review workflow from protocol to reporting.

"AI Literature Review Tools" (Webinar)

3:00pm-5:00pm EDT
May 12

Instructor: Steve Rokusek
Location: TBA
Goals:
Equip students and faculty with the knowledge and practical strategies needed to effectively use and critically evaluate AI-powered literature review tools.

Topics:

• Before AI: Traditional Library Databases
• The Rise of AI in Scholarly Discovery
• Categories of AI Tools for Scholarly Discovery
• Specific AI Tools for Finding Scholarly Sources
• Effective Prompting and Search Strategies
• Evaluating and Verifying AI-Generated Results
• Strengths, Limitations, and Responsible Use

"Your First (or Fastest) LaTeX Research Paper in 3 Hours" (Workshop)

9:00am-12:00pm EDT
May 13

Instructor: Md Baharul Islam
Location: TBA
Goals:
Participants will learn a fast, practical workflow to draft a publication-ready LaTeX paper and use AI responsibly to improve writing while verifying accuracy. 

Topics:

• LaTeX setup and workflow (Overleaf vs local)
• Paper template and structure (sections, formatting)
• Figures, tables, and equations (quick best practices)
• References and BibTeX (clean citations)
• Faster writing with AI (safe, practical prompts)
• Verification and academic integrity (avoid AI mistakes)
• Final checklist before submission (common pitfalls) 

"Artificial Intelligence and Cybersecurity" (Training)

9:00am-6:00pm EDT
May 14

Instructor: Chengyi Qu
Location: TBA
Goals:
The goal of this workshop is to equip participants with a clear understanding of how artificial intelligence can be effectively applied to modern cybersecurity challenges. Attendees will gain practical insights into AI-driven security techniques, recognize emerging threats such as adversarial AI, and learn how to design more resilient, ethical, and human-centered cybersecurity solutions for real-world systems

Topics:

• Fundamentals of AI in cybersecurity: opportunities, limitations, and threat models
• Machine learning and deep learning for intrusion detection and anomaly detection
• AI-enabled threat intelligence, malware analysis, and automated incident response
• Adversarial AI: evasion, poisoning attacks, and robustness of security models
• Edge/IoT and smart system security with AI-driven monitoring
• Human-centered AI and ethical considerations in cybersecurity applications

"Getting unstuck: Being prepared for future GenAI-AGI evolution in creative outcomes using abductive logics in research and teaching" (Workshop)

9:00am-12:00am EDT
May 18

Instructor: Mathew Sheep
Location: TBA
Goals:
Participants will engage in hands-on exercises to imagine possible AI futures as applied to the learner’s own context to prepare proactively for rapidly evolving AI landscapes with emerging competencies necessary to navigate them successfully.

Topics:

• Learning to think with abductive reasoning (the logic of possibilities) and future-making:  Imagining AI futures and learning what it means to “co-create forward” (Sharma, et al., 2022)
• Becoming unstuck: Moving gracefully from the static to the dynamic (earning the “silver star of adaptability”)
• Transitioning AI from tool to teammate, from co-pilot to coworker: Transitioning one’s engagement with AI as just another tool in one’s toolbox to AI as an autonomous, agentic teammate with whom humans collaborate
• “Leading from the future as it emerges” (Scharmer, 2009): A much-needed perspective in organizations for the “AI-Savvy Leader” (DeCremer, 2024)
• Implementing human-AI synergies in one’s own context: How might all of this actually play out in my world?

"Save Time Discovering Research with AI" (Webinar)

1:00pm-3:00pm EDT
May 18

Instructor: Rachel Cooke & Anna Carlin
Location: TBA
Goals:
Attendees will learn how to use select AI-powered tools to discover relevant literature and produce more comprehensive literature reviews.

Topics:

• Use ResearchRabbit to discover relevant literature through relational maps
• Connect citation management software Zotero with Research Rabbit
• Demonstrate pitfalls of using some generative AI tools for literature searching

"AI-Driven Software Testing in Action" (Training)

9:00am-6:00pm EDT
May 19

Instructor: Julio de Lima
Location: TBA
Goals:
AI-Driven Software Testing in Action is a practical, hands-on training that connects core software testing fundamentals with the real-world use of generative AI. Participants will learn how testers think, design, execute, and automate tests for Web applications — and how AI can be used as a collaborative assistant throughout the entire testing lifecycle. The training emphasizes critical thinking, solid testing techniques, and realistic automation practices, showing how AI boosts productivity without compromising quality or intent.

Topics:

• Foundations of Software Testing
• Applying Test Design Techniques with AI Assistance
• Creating and Reviewing Test Artifacts with AI
• Executing Web Tests with AI-Supported Exploration
• Writing High-Quality Defect Reports with AI
• Accelerating Web Test Automation with AI

"AI and Business Strategy: From Hype to Creating Value" (Training)

9:00am-6:00pm EDT
May 20

Instructor: Daniel Rottig
Location: TBA
Goals:
Equip participants with strategic frameworks, a critical perspective, and the practical knowledge needed to move beyond AI hype and deliberately use artificial intelligence to create real, sustainable value in organizations. 

Topics:

• AI Hype vs Strategic Reality: The Benefits and Limits of AI in Business Strategy and Why AI does not automatically create a competitive advantage
• When and Where AI Creates Value in the Strategic Management Process
• Evaluating AI as a Strategic Capability and Strategic Frameworks for AI Adoption, including Discovery-Driven Digital Transformation and AI-Driven Leadership
• From Artificial Intelligence to Augmenting Intelligence: Using AI Tools for Strategic Analysis and Decision Support to Augment (rather than Replace) Human Judgment
• Lessons from Real-World Cases of Successful and Failed AI-Driven Strategies
• Organizational, Leadership, and Governance Challenges in Turning AI into Strategic Value and the Future of AI in Strategic Management 

"Enhancing Education and Learning with AI Productivity Tools" (Workshop)

9:00am-12:00pm EDT
May 21

Instructor: Deepa Devasenapathy
Location: TBA
Goals:
Enable educators and learners to effectively use AI productivity tools to enhance teaching, learning, assessment, and academic workflows, while developing the ability to critically evaluate AI outputs and apply these tools responsibly in educational settings

Topics:

• AI Productivity Tools for Teaching and Learning: Overview of AI support for instruction, learning, and academic workflows
• Generative AI for Instruction, Study, and Assessment Support: Using ChatGPT and NoteGPT for explanations, summaries, practice, and feedback
• AI-Powered Content and Presentation Creation: Designing engaging lessons and slides using Gamma AI and Magic Slides

"Generative AI Beyond Text: Putting Image & Music Generators to the Test" (Workshop)

1:00pm-3:00pm EDT
May 21

Instructor: Jonathan H. Harwell
Location: TBA
Goals:
Challenge, evaluate, and think critically about AI tools that generate images and music, and consider their ethical implications for creative and academic contexts.

Topics:

• Overview of Generative AI Image and Music Tools
• Effective Prompting for Visual and Audio Generation
• Live Tool Demos and Experimentation
• Critically Evaluating AI-Generated Outputs
• Intellectual Property and Attribution
• Impacts on Creative Workers
• Responsible Use Guidelines

"AI Tools for Software Testing: Automating Web Application Testing" (Workshop)

9:00am-12:00pm EDT
May 22

Instructor: Deepa Devasenapthy
Location: TBA
Goals:
Equip participants with the knowledge and hands-on strategies needed to effectively use AI-powered tools 
to write efficient test cases, automate web application testing, improve test coverage, and enhance test
efficiency while understanding the limitations and best practices of AI-assisted testing.

Topics:

• Selenium WebDriver with AI-Assisted Script Development (GitHub Copilot / ChatGPT/ Claude AI)
• TestNG for Smart Test Execution and AI-Generated Test Scenarios
• Maven Build Automation with AI-Supported Dependency Management
• Jira for AI-Enhanced Defect Tracking and Test Case Generation
• Jenkins CI/CD Integration with AI-Driven Continuous Testing
• Self-Healing Automation Frameworks using Intelligent Locator Strategies
• End-to-End AI-Integrated Web Testing Pipeline (Selenium + TestNG + Maven + Jira)

"“I’m Afraid I Can’t Do That”: Engaging with Portrayals of AI in Pop Culture" (Workshop)

1:00pm-3:00pm EDT
May 22

Instructor: Jonathan H. Harwell
Location: TBA
Goals:
Explore how AI has been depicted in film across decades, and what those portrayals reveal about our evolving fears, values, and trust in technology.

Topics:

• Why Pop Culture Depictions of AI Matter
• AI on Screen: An Overview Across Decades
• Clip Screenings and Group Discussion
• Recurring Themes: Obedience, Rebellion, and Fear
• How Films Reflect Societal Values and Anxieties
• Fiction vs. Reality: Bridging Portrayals and Public Perceptions
• Contemporary Attitudes Toward Real-World AI

"AI for Everyday Life" (Training)

9:00am-11:00am EDT
May 26 - May 29

Instructor: Dr. Leandro de Castro
Location: TBA
Goals:
Help participants understand how AI systems influence daily life and equip them with practical strategies to use AI tools responsibly, safely, and effectively in various personal and professional contexts.

Topics:

• Where AI appears in everyday systems (search, recommendations, finance, healthcare, communication)
• Privacy, data protection, and digital footprint awareness
• Practical AI tools for productivity, planning, communication, and learning
• Bias, fairness, and responsible AI consumption
• AI literacy 
• Hands-on AI use-cases: traveling, cooking, healthcare, education, personal tutoring, etc.

"Applied Neural Networks: Theory, Training, and Hands-On Applications" (Training)

1:00pm-3:00pm EDT
May 26 - May 29

Instructor: Edumis Viera Martin
Location: TBA
Goals:
Develop participants’ ability to confidently build, evaluate, and apply neural network–based AI systems by understanding how they learn from data, preparing and splitting datasets effectively, constructing and testing models, identifying and addressing issues like overfitting, improving performance, and applying these skills to real-world tasks such as text and image classification.

Learning Outcomes:

• Foundations of Neural Networks: core concepts, architectures, and the mathematics behind how neural networks learn
• Training and Optimization of Neural Networks: loss functions, parameters, and optimization algorithms
• Hands-on Neural Network Development with Python: using Jupyter Notebooks to build and train real models
• Natural Language Processing Applications: text classification for tasks such as email filtering and news categorization
• Computer Vision Applications: image classification and visual pattern recognition with neural networks
• Model Evaluation and Performance Analysis: confusion matrices, classification reports, and accuracy metrics
• Generalization and Overfitting Control: techniques to improve model robustness and real-world performance

"Hands-On AI Workshop for Construction Professionals" (Workshop)

3:00pm-5:00pm EDT
May 27

Instructor: Anh D. Chau
Location: TBA
Goals:
Participants will learn to leverage AI tools for construction cost estimation and project planning through practical, hands-on applications

Topics:

• Overview of AI applications in construction industry.
• Hand-on activities in Togal.AI application for cost estimation.
• Hand-on activities on prompt engineering applications (e.g., RTF framework) in the construction industry. 

A Framework for Teaching with AI (Workshop)

2:00pm-6:00pm EDT
May 29

Instructor: Dr. Leandro de Castro
Location: TBA
Goals:
Equip instructors with a structured framework and practical design strategies to intentionally integrate generative AI into course design and assessment while preserving academic rigor, learner agency, and foundational disciplinary knowledge.

Topics:

• The Teaching with AI Framework 
• Operational AI Integration Across the Teaching Workflow
• Pedagogical Integration
  . Intentional role definition
  . Progressive integration
  . Productive friction
  . Prompt literacy
  . Verification-first
  . Hybrid assessment
  . Transparency, ethics, and professional accountability
• Instrumental Augmentation
  . Pedagogical planning
  . Class design
  . Assignment preparation
  . Class delivery
  . Student support
  . Assessment and feedback
  . Reflection and improvement

"Leading Human-centered AI Transformation: Start Here" (Webinar)

3:30pm-5:00pm EDT
May 7

Instructor: Angelo Biasi
Location: TBA
Goals:
To equip participants with a practical, human-centered lens for using AI to strengthen problem-solving, innovation, and real-world performance in ways that create meaningful and measurable impact.

Topics:

• Explain what human-centered AI transformation is and why it matters now.
• Distinguish AI adoption from true AI-enabled transformation.
• Identify the human capabilities that become more valuable in an AI-driven world.
• Use a practical framework for combining AI and human intelligence to solve real problems.
• Recognize how to build a culture of innovation with metrics that matter.
• Understand why evidence of applied skill matters more than content knowledge alone.