AI Fundamentals – Level 3 (2 Days) focuses on advanced, hands-on applications of AI for building tools, analyzing data, and creating interactive outputs. Participants learn how to move beyond traditional office software by generating HTML reports, custom data visualizations, and structured datasets using JSON—all with AI assistance. The emphasis is on producing dynamic, professional-grade outputs that are more flexible and powerful than standard documents or slides.
The course also introduces AI-assisted development, enabling participants to turn ideas into working applications using HTML and JavaScript without needing formal programming experience. In addition, it explores agentic AI concepts, showing how autonomous workflows can be designed to handle research, data processing, and repetitive tasks.
By the end of the course, participants will be able to build custom tools, automate complex workflows, and design AI-driven solutions tailored to their organization. They will also understand the risks, governance considerations, and future direction of advanced AI systems, positioning them to lead more sophisticated AI initiatives.
Course Outline
HTML Analysis and Reporting Skills
- Why HTML reports beat PDFs and PowerPoints for data communication
- Basic HTML structure: what you need to know (and what AI handles for you)
- Building a live, interactive report that opens in any browser
- Embedding charts, tables, and styling without writing CSS from scratch
- Sharing and distributing HTML reports within government networks
- Hands-on exercise: turn a dataset into a styled HTML dashboard
Make Any Chart
- Moving beyond Excel chart limitations
- Using AI to generate Chart.js, Plotly, and D3 visualizations
- Choosing the right chart type for your data and audience
- Customizing colors, labels, tooltips, and interactivity through prompts
- Responsive charts that work on any screen
- Hands-on exercise: build three chart types from the same dataset using AI
JSON Data Storage
- What JSON is and why it matters for modern data work
- Reading, writing, and structuring JSON files
- Using JSON as a lightweight data store for apps and reports
- Converting between CSV, Excel, and JSON formats with AI
- Hands-on exercise: structure a real dataset as JSON and build a report from it
Build Any App Idea
- From idea to working prototype: the AI-assisted development cycle
- Defining requirements in plain language
- Using AI to generate functional HTML/JavaScript applications
- Iterating: debugging, refining, and adding features through conversation
- Hands-on exercise: each participant builds a custom tool for their team
Agentic AI Knowledge
- What agentic AI means: autonomous workflows, tool use, and chaining
- How AI agents read files, search the web, and execute tasks
- Practical examples: automated research, document processing, data pipelines
- Limitations, risks, and governance considerations for autonomous AI
- Where this technology is heading and what it means for your work
- Hands-on exercise: design an agentic workflow for a real departmental process
Wrap-Up and Next Steps
- Review of the full AI 1–2–3 journey
- Open Q&A and portfolio review of everything built across three levels
- Course exam
- Certification pathway and continuing education options