AI Tools in Practice: ChatGPT, Claude & Gemini

In this lesson, you'll learn how to use Claude to effectively summarize large volumes of text. You'll learn why it's important to define the purpose and audience of a summary and how to create a prompt that gives you not just an answer, but a work-ready output.

This lesson shows you how to use Gemini in Google Workspace with maximum effectiveness. You'll learn how to turn simple queries into work-ready, structured outputs by optimizing your collaboration process with AI.

In this lesson, you'll learn how to use ChatGPT to create an effective email draft. We'll discuss how to move from a generic answer to a work-ready output using proper prompt structure and an iterative refinement process. The lesson emphasizes the importance of human editing and professional judgment when using AI.

In this lesson, you'll learn how to use Claude AI to refine the tone of existing text, especially emails. The focus will be on turning a plain answer into a work-ready, human, and recipient-tailored communication.

This lesson shows you how to use Gemini not just to summarize text, but to quickly turn chaotic meeting notes into an action card. You'll learn how to create work-ready outputs that clearly define decisions, tasks, blockers, and issues needing clarification.

In this lesson, you'll learn how to use ChatGPT not to get final answers, but to break down complex topics and map them into actionable research questions. You'll learn the difference between 'just getting an answer' and 'creating a work-ready output' when working with AI.

In this lesson, you'll learn how to use Claude AI to compare and analyze multiple sources. You'll learn how to move from 'just getting an answer' to 'creating a work-ready output' and how to refine your prompts for professional research.

In this lesson, you'll learn how to turn scattered research material into a concise, clear, and decision-oriented brief using Gemini. We'll discuss the difference between 'just getting an answer' and 'creating a work-ready output,' emphasizing proper prompt structure and the importance of human editing.

In this lesson, you'll learn how to use ChatGPT to explain complex pieces of code in plain language. We'll discuss creating effective prompts, the importance of an iterative approach, and the role of human editing in achieving a work-ready output.

In this lesson, you'll learn how to use Claude AI to improve the debugging process. We'll discuss why a structured description of the problem matters and how to achieve work-ready results when communicating with AI. The lesson will help you build a repeatable and effective debugging methodology.

This lesson explores how to use the Gemini AI model to quickly generate small code templates, structures, or starter code. The focus is on achieving a 'work-ready output' rather than blindly generating a complete system, emphasizing the importance of human editing and iterative prompting.

In this lesson, you'll learn how to compare ChatGPT, Claude, and Gemini on the same task. You'll learn not to search for a generally 'best' tool, but to select the most effective one for a specific context, based on output quality, speed, and fit with your workflow.

In this final lesson, you'll review what you've learned throughout the course and build your own AI tool-selection workflow map. You'll learn how to get not just answers, but work-ready outputs from AI tools through thoughtful choices and human editing.