2026-06: The AI Advantage: Understanding AI and Why It Matters to Me and My Organization (Webinar 1)
A beginner-friendly session introducing AI concepts, practical tools, responsible use, and real-world applications across personal, organizational, and sectoral contexts.
Learning Goals:
- Introduce AI and its benefits to persons and organizations
- For MSMEs: Set the mindset for AI project development for participating MSMEs and student teams
- Teacher: Aunhel John Adoptante
- Teacher: Antonio Briza
- Teacher: Samuel Harrison Cerrudo
- Teacher: Justin Parreño
Learning Goals:
- Identify AI project opportunity within one's organization
- Apply Design Thinking framework for AI Project ideation and execution
- Formulate an AI Project Statement
- Teacher: Aunhel John Adoptante
- Teacher: Antonio Briza
- Teacher: Jonathan Cempron
- Teacher: Samuel Harrison Cerrudo
- Teacher: Gary Chris Lacdang
- Teacher: Justin Parreño
- Teacher: Julius Noah Sempio
A practical walkthrough of rapid prototyping tools and AI-enabled application development approaches using LLM and agentic AI use cases.
Learning Goals:
- Introduce rapid prototyping tools
- Provide walkthrough illustrations of LLM/Agentic use cases for AI application development
- Teacher: Aunhel John Adoptante
- Teacher: Samuel Harrison Cerrudo
- Teacher: Gary Chris Lacdang
- Teacher: Justin Parreño
The webinar sessions will cover the following topics:
- Technical Introduction to AI – foundational concepts and approaches underlying modern AI systems;
- Data Management for AI – preparing, organizing, and managing data for effective AI development;
- The AI/ML Lifecycle – the major stages involved in developing, deploying, and maintaining AI/ML solutions;
- Classical Machine Learning Pipeline – an overview of the end-to-end process for building and evaluating classical machine learning models; and
- Explainable AI – approaches for understanding and interpreting AI/ML model outputs and decisions.
Through these sessions, participants will gain a more structured understanding of the technical foundations of AI/ML and the processes involved in translating data and organizational requirements into practical AI solutions.
A hands-on session on building practical AI applications using open-source models, lightweight deployment approaches, LLM integration, and agentic workflows.
Learning Goals:
- Use open-source AI models through platforms and tools such as Hugging Face and Ollama
- Deploy AI models as APIs or lightweight applications
- Integrate large language models into software applications and workflows
- Design and develop agentic AI applications that can use tools and execute multi-step tasks