Course Outline
Phase 1 — Getting to Know Claude Code — 55 minutes
- What Claude is and what distinguishes Claude Code from standard chat interfaces
- The Claude product ecosystem: claude.ai, Claude Desktop, and Claude Code (CLI), and their interconnections
- Interface tour: navigating the Claude app, initiating a coding session, and understanding the workspace
- How Claude Code operates: the describe → plan → act → review loop
- Understanding permissions: why Claude requests approval before creating files or running code
- Your first build: instructing Claude to create a simple styled webpage from a one-sentence description
- Iterating on results: refining outputs with instructions like “make the header larger,” “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 preferences in plain English. They practice refining their results through follow-up instructions.
Goal: ensuring everyone is comfortable with the interface and overcomes 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 tasks of increasing complexity using only natural language prompts.
- Task 1 — Interactive dashboard: instruct 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 the 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, a project status update, or a meeting recap. This shows how Claude can transform raw data into polished deliverables.
- Task 4 — Automation tool: ask Claude to build a simple utility — such as a unit converter, a quiz app, or a budget calculator. This introduces the concept that Claude can build interactive tools, not just static pages.
After each task, the instructor highlights Claude’s background processes: 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 effective prompting: distinguishing between specific and vague instructions
- Live demo: side-by-side comparison of weak and strong prompts applied to the same task
- Iterating and refining: asking Claude to explain its choices, undo changes, or explore alternative approaches
- Working with uploaded files: instructions like “read this document and summarize it” or “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
- When to use Claude Code versus 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 drove the improvement.
Goal: elevating skills 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 room’s energy. Instead of individual practice, the group builds together. The instructor leads the session, but participants control the direction by naming real problems from their jobs, suggesting prompt ideas, and debating trade-offs. The goal is to learn prompt judgment by observing an expert navigate uncertainty in real time.
Three workflow archetypes structure the session:
- Transform — converting input X into output Y (meeting notes → action items; raw data → summary email; customer feedback → themed report)
- Draft — generating a first version of content you would normally write from scratch (proposals, emails, job descriptions, social media posts)
- Analyze — interrogating a document or dataset you do not have time to review carefully (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 format. 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 group suggesting prompts, pushing back, and refining ideas. The instructor narrates every decision. The session ends with a working prompt template that the participant whose problem it was keeps.
Live build #2 — Draft or Analyze workflow (20 min): Follows the same format but focuses on a different archetype and another participant’s problem.
Reflection & share-back (10 min): Participants write down one prompting move that surprised them, one thing they would do differently, and one pattern they will take home. A quick group share follows, featuring 3-4 voices. The instructor connects these 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: 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 required)
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 varying comfort levels:
- Option A: Connect a pre-built connector from the directory (e.g., Gmail, Google Drive, or a demo service) — click, authenticate, and start
- 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 give 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 function: 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: helping 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 selects 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 workflow problem (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 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 — what each tier unlocks and which fits specific use cases
- Best practices recap: the Prompt Playbook patterns that proved most effective during the session
- Recommended resources: official documentation, community channels, and 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
Understanding of
- Basic computer literacy: navigating files and folders, using a web browser, and installing applications
- General awareness of AI assistants (e.g., casual use of ChatGPT, Gemini, or Claude is helpful but not mandatory)
Experience with
- No coding, programming, or terminal experience is required. This course is specifically designed for individuals who have never written code.
- No prior experience with Claude or any other AI tool is necessary.
Technical Requirements
- 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 registration; setup instructions are provided beforehand)
- Claude Desktop is recommended but not mandatory (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), although alternative connector options are available
Target Audience
- Business professionals aiming to leverage AI for productivity and automation
- Marketers, operations managers, and analysts seeking to automate repetitive tasks
- Founders and entrepreneurs wanting to build prototypes without hiring developers
- Educators and researchers exploring AI-assisted workflows
- Anyone with no technical background who is curious about what Claude can create
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
