Course Outline
Phase 1 — Meet Claude Code — 55 minutes
- An overview of what Claude is and how Claude Code differs from standard chat.
- The Claude product family: claude.ai, Claude Desktop, and Claude Code (CLI), and their relationships.
- Interface tour: navigating the Claude app, initiating a coding session, and understanding the workspace.
- Understanding Claude Code’s thought process: the describe → plan → act → review loop.
- Permissions explained: why Claude asks for confirmation before creating files or running code.
- Your first build: instructing Claude to create a simple styled webpage from a brief description.
- Iterating on results: refining outputs with prompts 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 preferences in plain English. They practice refining results through follow-up instructions.
Goal: Ensure everyone is comfortable with the interface and has overcome the initial interaction hurdle.
Break — 10 minutes
Phase 2 — Building Real Things with Plain English — 70 minutes
This segment forms the core of the morning session. Participants complete four progressively complex tasks 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,” “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/lowest values, and generate a visual chart. This 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 — such as a sales summary, project status update, or meeting recap. This shows how Claude transforms raw data into polished deliverables.
- Task 4 — Automation tool: Instruct Claude to build a simple utility — 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 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.
Break — 10 minutes
Phase 3 — Working Smarter with Claude Code — 50 minutes
- The art of effective prompting: balancing specific vs. vague instructions.
- Live demo: A 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 attempt alternative approaches.
- Working with uploaded files: Examples include “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 costs and usage: How tokens, context windows, and subscription tiers function.
- When to choose Claude Code versus regular Claude chat.
- Guided exercise: Participants select one Phase 2 project 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: Progress from “it works” to “I can consistently achieve great results.”
Break — 10 minutes
Phase 4 — Your Claude Workflows: Live Build Session — 60 minutes
This phase shifts the room’s energy. Instead of solo practice, the group builds together. While the instructor drives the technical execution, participants control the direction by proposing real problems from their jobs, suggesting prompt ideas, and debating trade-offs. The objective is to learn prompt judgment by observing an expert navigate uncertainty in real-time.
Three workflow archetypes structure this session:
- Transform — Convert input X into output Y (e.g., meeting notes to action items; raw data to a summary email; customer feedback to a themed report).
- Draft — Generate a first version of content typically written from scratch (proposals, emails, job descriptions, social media posts).
- Analyze — Interrogate a document or dataset that is too large 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 format. Participants submit real workflow challenges 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 suggesting prompt ideas, pushbacks, and refinements. The instructor narrates every decision. The session ends with a working prompt template that the original contributor keeps.
Live build #2 — Draft or Analyze workflow (20 min): Same format, different archetype, addressing another participant’s problem.
Reflection & share-back (10 min): Participants jot down one prompting move that surprised them, one thing they would do differently, and one pattern they will adopt. A quick group share follows — 3-4 participants speak, not everyone. 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 within the Claude app.
- Desktop Extensions: One-click installs for Claude Desktop (no configuration files required).
Live demo: The instructor connects Claude to two services via 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, choosing from options based on their comfort level:
- Option A: Connect a pre-built connector from the directory (e.g., Gmail, Google Drive, or a demo service) — simply 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 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 discover new connectors, extensions, and community-built servers.
Goal: Participants view Claude as a connective layer between all their existing services, not merely as a coding tool.
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: uploading a file, having Claude analyze it, and producing a visual report.
- An interactive tool that solves a real workflow problem (calculator, tracker, converter, quiz).
- A connected workflow: pulling data from a linked service, transforming it, and producing a deliverable (e.g., “read my calendar for next week and build a visual schedule.”)
The instructor circulates the room 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, Cowork for knowledge workers.
- The MCP ecosystem: How to find and evaluate new connectors, extensions, and community servers.
- Pricing plans: Free vs. Pro vs. Max — understanding what each unlocks and which fits specific use cases.
- Best practices recap: Reviewing 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 containing key prompting patterns, connector setup steps, and a curated list of useful MCP integrations.
Requirements
Requirements
You should have an understanding of
- Basic computer literacy: navigating files and folders, using a web browser, and installing applications
- A general awareness of what AI assistants do (e.g., having casually used ChatGPT, Gemini, or Claude provides helpful context but is not mandatory)
No prior experience with the following is needed
- Coding, programming, or terminal usage. This course is tailored for individuals who have never written a line of code.
- Prior familiarity with Claude or any other AI tool.
Technical Requirements
- Participants must bring a laptop (Mac, Windows, or Linux) equipped with a modern web browser.
- A stable internet connection is required.
- A Claude Pro subscription for the session (a 1-month gift subscription is included with registration; setup instructions are provided prior to class).
- While Claude Desktop is recommended, it is not mandatory; the web app at claude.ai supports all exercises.
- A Google account is suggested for the MCP connectors exercise (Gmail, Google Drive, Google Calendar), though alternative connector options are available.
Target Audience
- Business professionals seeking to leverage AI for productivity and automation.
- Marketers, operations managers, and analysts looking to automate repetitive tasks.
- Founders and entrepreneurs who wish to build prototypes without hiring a developer.
- Educators and researchers exploring AI-assisted workflows.
- Anyone curious about Claude’s capabilities but lacking 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
