AI Prompt Engineering with ChatGPT, Gemini, and Claude

Unmanaged AI use can create inconsistent outputs, rework, and data-handling risk across a technical team. This beginner course gives IT Directors and Training Managers a practical way to standardize how teams use ChatGPT, Gemini, and Claude for day-to-day work. In about 4 hours and 49 minutes per learner, IT Practitioners build a shared prompt vocabulary: AI fundamentals, workspace guardrails, CRE prompt structure, few-shot examples, role-guided templates, grounding, paste-in retrieval (RAG), and better use of context. It fits teams that are already experimenting with AI and need safer, repeatable habits before broader rollout. For change management, assign it as a baseline before teams create internal prompt templates or AI usage guidelines. CBT Nuggets Playlists can help organize rollout by team, and Team Reporting helps leaders track completion.

This training helps teams move from ad hoc AI experimentation to more consistent, governed use of common AI tools. The course focuses on practical prompting patterns teams can apply across ChatGPT, Gemini, and Claude.

• Set up chat workspaces with guardrails so teams can reduce avoidable risk when using AI tools.
• Build clearer prompts using CRE structure and examples, helping reduce back-and-forth and inconsistent responses.
• Create reusable role-guided templates that support repeatable team workflows instead of one-off prompts.
• Improve answer quality by grounding prompts with pasted-in source material, retrieval-style context, and better context management.

Knowledge

• Core AI and prompt engineering fundamentals.
• How guardrails support safer AI workspace habits.
• How CRE prompt structure and “shots” improve prompt clarity.
• How role guidance shapes more useful AI responses.
• How grounding, paste-in retrieval, and context affect output quality.

Ability

• Configure a practical chat workspace with team-appropriate guardrails.
• Write prompts for ChatGPT, Gemini, and Claude using repeatable structures.
• Build prompt templates guided by roles and examples.
• Ground AI responses with pasted-in reference material.
• Adjust context to get more relevant, usable AI outputs.