Course Outline
Phase 1 — Meet Claude Code — 55 minutes
- Understanding what Claude is and how Claude Code differs from standard chat.
- Overview of the Claude product family: claude.ai, Claude Desktop, Claude Code (CLI), and their relationships.
- Interface tour: Navigating the Claude app, initiating a coding session, and understanding the workspace.
- The Claude Code thought process: The describe → plan → act → review loop.
- Understanding permissions: Why Claude asks for confirmation before creating files or executing code.
- First build: Asking Claude to create a simple styled webpage based on a one-sentence description.
- Iterating on results: Refining outputs with instructions like “make the header bigger,” “change the color scheme,” or “add a navigation bar.”
- Guided exercise: Participants open the Claude app, start a Claude Code session, and build a personalized “About Me” webpage by describing their requirements in plain English. They practice refining results through follow-up instructions.
Goal: Ensure everyone is comfortable with the interface and has overcome the initial learning curve.
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Break — 10 minutes |
Phase 2 — Building Real Things with Plain English — 70 minutes
This phase forms the core of the morning session. Participants complete four progressively complex tasks using only natural language prompts.
- Task 1 — Interactive dashboard: Request Claude Code to build a styled dashboard displaying sample data with charts, statistics, and a clean layout. Practice providing design direction: “use a dark theme,” “add a sidebar,” or “make it responsive.”
- Task 2 — Data analysis: Provide Claude with a sample CSV file and ask it to summarize the data, identify trends, find highest and lowest values, and generate a visual chart. This demonstrates Claude’s ability to write and execute code on your behalf.
- Task 3 — Document generator: Ask Claude to read a data file and produce a formatted report — such as a sales summary, project status update, or meeting recap. This illustrates how Claude transforms raw data into polished deliverables.
- Task 4 — Automation tool: Ask Claude to build a simple utility — such as a unit converter, quiz app, or budget calculator. This introduces the concept that Claude can create interactive tools, not just static pages.
After each task, the instructor highlights Claude’s backend actions: which files were created, what code was written, and how to interpret the output. Participants document their most effective prompts in a shared Prompt Playbook.
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Break — 10 minutes |
Phase 3 — Working Smarter with Claude Code — 50 minutes
- The art of good prompting: Differentiating between specific and vague instructions.
- Live demo: Side-by-side comparison of weak versus strong prompts on the same task.
- Iterating and refining: Asking Claude to explain its reasoning, undo changes, or try alternative approaches.
- Working with uploaded files: Examples include “read this document and summarize it,” and “convert this spreadsheet into a chart.”
- Multi-step workflows: Chaining requests to create complex outputs (e.g., “first analyze this data, then build a dashboard from the results.”)
- Understanding cost and usage: How tokens, context windows, and subscription tiers function.
- Determining when to use Claude Code versus standard Claude chat.
- Guided exercise: Participants take one of their Phase 2 projects and extend it with two new features using a multi-step prompt chain. They then compare their before-and-after prompts to identify key differences.
Goal: Move from “it works” to “I can consistently achieve great results.”
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Break — 10 minutes |
Phase 4 — Your Claude Workflows: Live Build Session — 60 minutes
This phase shifts the energy in the room. Instead of solo practice, the group builds together. While the instructor leads the technical execution, participants drive the process by suggesting real workplace problems, proposing prompt ideas, and debating trade-offs. The objective is to learn prompt judgment by observing how an expert navigates uncertainty in real time.
Three workflow archetypes structure the session:
- Transform — Convert input X into output Y (e.g., meeting notes → action items; raw data → summary email; customer feedback → themed report).
- Draft — Generate a first version of content you would typically write from scratch (e.g., proposals, emails, job descriptions, social media posts).
- Analyze — Interrogate a document or dataset you don’t have time to review carefully (e.g., a 40-page report, a spreadsheet of survey responses, a contract).
Setup and framing (10 min): The instructor introduces the three archetypes and explains the session mechanics. Participants submit real workflow problems from their jobs via a shared document or chat.
Live build #1 — Transform workflow (20 min): The instructor selects one submitted problem and builds it live, with the room providing prompt ideas, pushbacks, and refinements. The instructor narrates every decision, ending with a working prompt template that the participant whose problem was selected gets to keep.
Live build #2 — Draft or Analyze workflow (20 min): Same format, but focusing on a different archetype and a different participant’s problem.
Reflection & share-back (10 min): Participants take a moment to note one prompting move that surprised them, one thing they’d do differently, and one pattern they’re taking home. A quick group share follows (3-4 voices, not everyone). The instructor connects these observations to the broader Prompt Playbook.
Phase 5 — Connecting Claude to Your Tools with MCP — 50 minutes
- Understanding MCP (Model Context Protocol): The universal plug system for AI tools.
- Why MCP matters: Transforming Claude from a chat assistant into a connected workflow hub.
- The Connectors Directory: Browsing and adding integrations directly from the Claude app.
- Desktop Extensions: One-click installs for Claude Desktop (no configuration files needed).
Live demo: The instructor connects Claude to two services through the Connectors UI and demonstrates cross-tool workflows:
- “Check my Google Calendar for tomorrow’s meetings and draft a prep email for each one.”
- “Read the latest updates from our project board and write a status summary.”
- “Pull data from this connected service and build a local report from it.”
Guided exercise: Participants connect Claude to at least one service. Options are provided for different comfort levels:
- Option A: Connect a pre-built connector from the directory (e.g., Gmail, Google Drive, or a demo service) — click, authenticate, and go.
- Option B: Add a custom connector by pasting an MCP server URL (the instructor provides a test URL).
- Option C: Install a Desktop Extension from the marketplace (for Claude Desktop users).
Participants then assign Claude a task that utilizes the connected service — for example, “Read my recent emails about project updates and create a summary document.”
Key concepts covered:
- How connectors work: OAuth authentication, permissions, and the scope of access granted.
- Managing tool access: Enabling, disabling, and controlling which connectors Claude can use per conversation.
- Security awareness: Connecting only to trusted services and reviewing tool permissions.
- The MCP ecosystem: Where to find new connectors, extensions, and community-built servers.
Goal: Participants view Claude as a connective layer between all the services they already use, rather than just a coding tool.
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Break — 10 minutes |
Phase 6 — Capstone & Next Steps — 65 minutes
Capstone mini-project (45 min): Each participant chooses one scenario and builds it with Claude:
- A polished landing page or portfolio site for their team, project, or personal brand.
- A data analysis pipeline: Upload a file, have Claude analyze it, and produce a visual report.
- An interactive tool that solves a real problem from their workflow (calculator, tracker, converter, or quiz).
- A connected workflow: Pull data from a connected service, transform it, and produce a deliverable (e.g., “read my calendar for next week and build a visual schedule.”)
The instructor circulates to help refine prompts and showcases standout examples to the group.
Showcase and wrap-up (20 min):
- 6-8 participants share what they built (2-3 minutes each).
- Where to go from here: Claude Code CLI for terminal users, VS Code extension for developers, and Cowork for knowledge workers.
- The MCP ecosystem: Finding and evaluating new connectors, extensions, and community servers.
- Plans: Free vs. Pro vs. Max — understanding what each tier unlocks and which fits which use case.
- Best practices recap: Reviewing the Prompt Playbook patterns that worked best during the session.
- Recommended resources: Official documentation, community channels, and Anthropic’s prompt engineering guide.
- Participants receive a reference card containing key prompting patterns, connector setup steps, and a curated list of useful MCP integrations.
Requirements
Requirements
Prerequisite Knowledge
- Basic computer literacy: Ability to navigate files and folders, use a web browser, and install applications.
- General awareness of AI assistant capabilities (e.g., casual use of ChatGPT, Gemini, or Claude is beneficial context, though not mandatory).
Required Experience
- No coding, programming, or terminal experience is needed. This course is specifically designed for individuals who have never written a line of code.
- Prior experience with Claude or any other AI tool is not required.
Technical Requirements
- Participants must bring a laptop (Mac, Windows, or Linux) equipped with a modern web browser.
- A stable internet connection.
- A Claude Pro subscription for the session (a 1-month gift subscription is included with registration; setup instructions are provided prior to the class).
- Claude Desktop is recommended but optional; the web app at claude.ai is sufficient for all exercises.
- A Google account is recommended for the MCP connectors exercise (for Gmail, Google Drive, and Google Calendar), although alternative connector options are available.
Target Audience
- Business professionals seeking to leverage AI for productivity and automation.
- Marketers, operations managers, and analysts aiming to automate repetitive tasks.
- Founders and entrepreneurs looking to build prototypes without hiring developers.
- Educators and researchers exploring AI-assisted workflows.
- Anyone interested in what Claude can build who lacks a technical background.
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
