# AI & Data Literacy for the Federal Workforce (Self-Paced)

Canonical URL: <https://www.nobledesktop.com/classes/ai-data-literacy-for-the-federal-workforce-self-paced>

## Overview

AI and data are transforming how organizations operate and make decisions. This interactive training grounds participants in the essentials of AI and data literacy, giving them the tools to confidently work with data-driven technologies in their daily roles.

Through guided activities and practical examples, participants will explore core concepts, common terminology, and best practices for applying AI tools and making sense of data. With a focus on real-world use, the course delivers actionable strategies that strengthen digital confidence, sharpen decision-making, and help cultivate a more data-savvy workplace.

## What you'll learn

- Define basic concepts and terminology tied to artificial intelligence and data
- Recognize how AI and data show up in workplace operations and decision-making
- Make sense of simple data visualizations and AI output you'll run into in everyday work
- Spot the common risks and ethical considerations that come with AI and data use
- Put foundational practices to work to build your data literacy and back responsible AI use

## Curriculum

#### Module 1: AI Foundations & Why Verification Comes First

- Core AI and data concepts: algorithms, models, structured vs. unstructured data
- Where AI training data comes from — and why it matters for output quality
- The AI Validation Checklist: a seven-point verification framework
- What hallucinations look like in practice — and why they're dangerous
- The DIG framework: Describe, Introspect, Goal-Set before every AI analysis
- The AI Decision Log: documenting prompts, output, verification, and decisions

#### Module 2: AI in Government & Interpreting Data

- AI in government operations: fraud detection, document automation, chatbots, predictive analytics
- Human-AI partnership: why human oversight isn't optional
- The ACHIEVE framework: deciding when to use AI
- Common chart types and how to read them critically
- Common pitfalls in data interpretation: correlation vs. causation, misleading averages, and more
- Interpreting AI output: prediction scores, category labels, and generated insights

#### Module 3: Responsible AI & Ethics

- Current federal AI policy direction and the March 2026 national framework
- Bias and fairness: real examples from TSA, healthcare, and criminal justice
- Deepfakes and synthetic media: risks and protective practices for federal employees
- Data privacy and PII awareness: what to share and what to protect
- How the AI Decision Log connects to accountability, transparency, and FOIA readiness

#### Module 4: Practical Skills & Your Action Plan

- Prompt engineering: weak vs. strong prompts with federal examples
- The RACE prompt framework: Role, Action, Context, Expectation
- Generative AI in your federal workflow: where AI helps vs. where humans must decide
- Hands-on lab: Use AI to analyze a federal operations dataset using DIG, RACE, and the Validation Checklist
- Know your agency's AI landscape: Chief AI Officer, approved tools, governance structure
- AI and data literacy by role: how today's skills apply to your specific job function

## Pricing

**Tuition:** $675