Course Outline
Day 1 – Using Claude Effectively for Everyday Business Work
Module 1 – Introduction to Claude
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What is Claude?
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How Large Language Models (LLMs) work
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Claude's strengths and limitations
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Choosing the appropriate Claude model
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Privacy, security, and responsible AI use
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Working with conversations, files, and context
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Understanding Claude Projects and Artifacts
Hands-on: Exploring the Claude interface and completing first business tasks.
Module 2 – Prompt Engineering Fundamentals
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What makes an effective prompt
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Structuring prompts for better results
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Providing context and defining objectives
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Assigning roles and personas
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Specifying output formats
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Iterative prompting and prompt refinement
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Creating reusable prompt templates
Hands-on: Creating prompts for emails, reports, summaries, and business documents.
Module 3 – Claude for Business Productivity
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Document drafting and editing
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Report generation
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Meeting summaries and action plans
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Research and information synthesis
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Working with spreadsheets and structured data
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Organizing and cleaning datasets
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Generating tables and business documentation
Hands-on: Processing real business documents and datasets using Claude.
Module 4 – Claude Projects
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Creating and organizing Claude Projects
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Building reusable knowledge bases
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Managing project instructions
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Using project-specific context
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Creating reusable business assistants
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Maintaining consistency across recurring tasks
Hands-on: Creating a personalized Claude Project tailored to each participant's role.
Day 2 – Understanding and Designing AI Agents with Claude
Module 5 – Introduction to AI Agents
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What is an AI agent?
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AI assistants vs. workflows vs. AI agents
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Business value of AI agents
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Common business use cases
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Identifying suitable processes for automation
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Understanding the capabilities and limitations of AI agents
Hands-on: Evaluating business scenarios to determine where AI agents can add value.
Module 6 – How AI Agents Work
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Goals, instructions, and decision-making
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Context, memory, and knowledge
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Inputs and outputs
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Human oversight and validation
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Reasoning and iterative improvement
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The lifecycle of an AI agent
Instructor Demonstration: Following an AI agent from request to completed task.
Module 7 – Anatomy of an AI Agent
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Breaking down a real business AI agent
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Understanding prompts, instructions, and knowledge sources
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Designing workflows and decision logic
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Testing and refining an agent
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Best practices for creating reliable AI agents
Hands-on: Analyzing and improving the design of an existing AI agent.
Module 8 – Designing AI Agents with Claude
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Designing AI agents using natural language
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Defining business objectives and success criteria
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Structuring workflows without programming
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Creating reusable AI assistants
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Refining AI-generated workflows
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Common design mistakes and how to avoid them
Hands-on: Using Claude to design and refine a no-code AI agent.
Module 9 – AI Agent Design Workshop
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Identifying a real business process suitable for automation
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Mapping inputs, outputs, and decision points
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Designing an AI agent for a business scenario
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Reviewing and refining agent designs
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Next steps for implementing AI agents after the training
Workshop: Participants create a blueprint for an AI agent tailored to their own role or department, providing a practical foundation for developing and deploying similar solutions within their organization after the course.
Requirements
No prior knowledge or experience with Claude is required.
