Course Outline
Phase 1 — Meet Claude Code — 55 minutes
- What Claude is, and what makes Claude Code different from regular chat
- The Claude product family: claude.ai, Claude Desktop, Claude Code (CLI), and how they relate
- Interface tour: navigating the Claude app, starting a coding session, and understanding the workspace
- How Claude Code thinks: the describe → plan → act → review loop
- Understanding permissions: why Claude asks before creating files or running code
- Your first build: asking Claude to create a simple styled webpage from a one-sentence description
- Iterating on results: “make the header bigger,” “change the color scheme,” “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 what they want in plain English. They practice refining their results through follow-up instructions.
Goal: everyone is comfortable with the interface and past the first-interaction hurdle.
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Break — 10 minutes |
Phase 2 — Building Real Things with Plain English — 70 minutes
This is the core of the morning. Participants complete four progressively complex tasks using only natural language prompts.
- Task 1 — Interactive dashboard: ask Claude Code to build a styled dashboard that displays sample data with charts, stats, and a clean layout. Practice giving design direction: “use a dark theme,” “add a sidebar,” “make it responsive.”
- Task 2 — Data analysis: provide Claude with a sample CSV file and ask it to summarize the data, identify trends, find the highest and lowest values, and generate a visual chart. Demonstrates how Claude writes and executes code on your behalf.
- Task 3 — Document generator: ask Claude to read a data file and produce a formatted report — a sales summary, a project status update, or a meeting recap. Shows how Claude can transform raw data into polished deliverables.
- Task 4 — Automation tool: ask Claude to build a simple utility — a unit converter, a quiz app, or a budget calculator. Introduces the idea that Claude can build interactive tools, not just static pages.
After each task, the instructor highlights what Claude did behind the scenes: which files it created, what code it wrote, and how to read the output. Participants document their best 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: specific vs. vague instructions
- Live demo: side-by-side comparison of weak and strong prompts on the same task
- Iterating and refining: asking Claude to explain its choices, undo changes, or try a different approach
- Working with uploaded files: “read this document and summarize it,” “convert this spreadsheet into a chart”
- Multi-step workflows: chaining requests to build complex outputs (“first analyze this data, then build a dashboard from the results”)
- Understanding cost and usage: how tokens, context windows, and subscription tiers work
- When to use Claude Code vs. regular 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 what made the difference.
Goal: level up from “it works” to “I can get great results consistently.”
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Break — 10 minutes |
Phase 4 — Your Claude Workflows: Live Build Session — 60 minutes
This phase shifts energy in the room. Instead of solo practice, the group builds together. The instructor drives, but participants call the shots — naming real problems from their own jobs, suggesting prompt ideas, debating tradeoffs. The goal is to learn prompt judgment by watching someone skilled navigate uncertainty in real time.
Three workflow archetypes structure the session:
- Transform — take input X, produce output Y (meeting notes → action items; raw data → summary email; customer feedback → themed report)
- Draft — generate a first version of something you’d normally write from scratch (proposals, emails, job descriptions, social posts)
- Analyze — interrogate a document or dataset you don’t have time to read carefully (a 40-page report, a spreadsheet of survey responses, a contract)
Setup and framing (10 min): Instructor introduces the three archetypes and explains how the session works. Participants submit real workflow problems from their jobs via a shared doc or chat.
Live build #1 — Transform workflow (20 min): Instructor picks one submitted problem, builds it live with the room calling out prompt ideas, pushbacks, and refinements. Instructor narrates every choice. Ends with a working prompt template that the participant whose problem it was gets to keep.
Live build #2 — Draft or Analyze workflow (20 min): Same format, different archetype, different participant’s problem.
Reflection & share-back (10 min): Participants take a moment to write down one prompting move that surprised them, one thing they’d do differently, and one pattern they’re taking home. Quick group share — 3-4 voices, not everyone. Instructor connects observations to the broader Prompt Playbook.
Phase 5 — Connecting Claude to Your Tools with MCP — 50 minutes
- What is MCP (Model Context Protocol)? The universal plug system for AI tools
- Why MCP matters: turning 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: 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 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 (instructor provides a test URL)
- Option C: Install a Desktop Extension from the marketplace (Claude Desktop users)
Participants then give Claude a task that uses the connected service — e.g., “Read my recent emails about project updates and create a summary document.”
Key concepts covered:
- How connectors work: OAuth authentication, permissions, and what access you are granting
- 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 see Claude as a connective layer between all the services they already use, not 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, 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, helps refine prompts, and showcases standout examples to the group.
Showcase and wrap-up (20 min):
- 6-8 participants share what they built (2-3 min each)
- Where to go from here: Claude Code CLI for terminal users, VS Code extension for developers, Cowork for knowledge workers
- The MCP ecosystem: finding and evaluating new connectors, extensions, and community servers
- Plans: Free vs. Pro vs. Max — what each unlocks and which fits which use case
- Best practices recap: the Prompt Playbook patterns that worked best during the session
- Recommended resources: official documentation, community channels, Anthropic’s prompt engineering guide
- Participants receive a reference card with key prompting patterns, connector setup steps, and a curated list of useful MCP integrations
Requirements
Requirements
An understanding of
- Basic computer literacy: navigating files and folders, using a web browser, and installing applications
- General awareness of what AI assistants do (e.g., having used ChatGPT, Gemini, or Claude casually is helpful context, but not required)
Experience with
- No coding, programming, or terminal experience required. This course is designed for people who have never written a line of code.
- No prior experience with Claude or any AI tool is necessary.
Technical requirements
- Participants should bring a laptop (Mac, Windows, or Linux) with a modern web browser
- A stable internet connection
- A Claude Pro subscription for the session (a 1-month gift subscription is included with course registration; setup instructions are sent before class)
- Claude Desktop is recommended but not required (the web app at claude.ai is sufficient for all exercises)
- A Google account is recommended for the MCP connectors exercise (Gmail, Google Drive, Google Calendar), but alternative connector options are available
Audience
- Business professionals looking to leverage AI for productivity and automation
- Marketers, operations managers, and analysts who want to automate repetitive tasks
- Founders and entrepreneurs who want to build prototypes without hiring a developer
- Educators and researchers exploring AI-assisted workflows
- Anyone curious about what Claude can build who has no technical background
Testimonials (2)
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
Michal Maj - XL Catlin Services SE (AXA XL)
Course - GitHub Copilot for Developers
Trainer able to adjust the course level during training to fit our understanding level on the topic, so that we could gain more useful knowledge that could further help us harness the tools in our daily works.
