Course Outline
Phase 1 — Meet Claude Code — 30 minutes
- What Claude is and how it differs from standard chat interfaces.
- Quick orientation: using the Claude app today (web or desktop); CLI and other interfaces are covered in the reference card.
- Interface tour: starting a coding session and understanding the workspace.
- How Claude Code thinks: the describe → plan → act → review cycle.
- Understanding permissions: why Claude requests approval 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: refining with instructions like “make the header bigger,” “change the color scheme,” or “add a navigation bar.”
- Guided exercise: participants start a session to build a personalized “About Me” webpage, refining it through follow-up instructions.
Goal: Ensure everyone passes the initial interaction hurdle and feels comfortable with the interface.
Break — 7 minutes
Phase 2 — Building Real Things with Plain English — 55 minutes
Three progressively complex tasks using only natural language prompts.
- Task 1 — Interactive dashboard: Create a styled dashboard with sample data, charts, and statistics. Practice providing design direction: “use a dark theme,” “add a sidebar,” “make it responsive.”
- Task 2 — Data analysis: Provide a sample CSV, ask Claude to summarize, identify trends, find highs/lows, and generate a visual chart. This demonstrates Claude writing and executing code on your behalf.
- Task 3 — Automation tool: Build a simple utility — such as a unit converter, quiz app, or budget calculator. This introduces the concept that Claude can build interactive tools, not just static pages.
After each task, the instructor highlights what happened behind the scenes: files created, code written, and how to interpret the output. Participants document their most effective prompts in a shared Prompt Playbook.
Break — 7 minutes
Phase 3 — Working Smarter with Claude Code — 35 minutes
- The art of effective prompting: specific vs. vague instructions.
- Live demo: side-by-side comparison of weak and strong prompts for the same task.
- Iterating and refining: asking Claude to explain choices, undo changes, or try a different approach.
- Working with uploaded files: examples like “read this document and summarize it” or “convert this spreadsheet into a chart.”
- Multi-step workflows: chaining requests to create complex outputs.
- Understanding cost and usage: how tokens, context windows, and subscription tiers work.
- When to use Claude Code versus regular Claude chat.
- Guided exercise: participants extend one of their Phase 2 projects with a new feature using a multi-step prompt, then compare before-and-after prompts to identify what made the difference.
Goal: Elevate from “it works” to “I can achieve great results consistently.”
Break — 7 minutes
Phase 4 — Connecting Claude to Your Tools with MCP — 34 minutes
Pre-class: Participants received emails with instructions to connect Gmail or Google Drive before the session, allowing classroom time to focus on using the connection rather than authentication.
- 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 users).
- Live demo (one workflow): “Check my Google Calendar for tomorrow’s meetings and draft a prep email for each one.”
- Guided exercise: participants use their pre-connected service (or connect one live) to give Claude a task — e.g., “Read my recent emails about project updates and create a summary document.”
- Key concepts: OAuth, permissions, managing tool access per conversation, security awareness, and where to find new connectors.
Goal: Help participants view Claude as a connective layer, not just a coding tool.
Phase 5 — Capstone & Wrap-Up — 35 minutes
Capstone mini-project (25 min): Each participant chooses one scenario:
- A polished landing page or portfolio site.
- A data analysis pipeline: upload a file, analyze it, produce a visual report.
- An interactive tool solving a real problem from their workflow.
- A connected workflow: pull data from the service connected in Phase 4, transform it, and produce a deliverable.
The instructor circulates to help refine prompts and showcase standout examples.
Wrap-up (10 min):
- Next steps: Claude Code CLI for terminal users, VS Code extension for developers, Cowork for knowledge workers.
- Plans: Free vs. Pro vs. Max — what each unlocks and which fits which use case.
- Recommended resources: official docs, Anthropic’s prompt engineering guide, community channels.
- Participants leave with a reference card covering prompting patterns, connector setup, and useful MCP integrations.
Requirements
Requirements
An understanding of
- Basic computer literacy: navigating files and folders, using a web browser, and installing applications
- A general awareness of AI assistants (e.g., casually using ChatGPT, Gemini, or Claude is helpful context, but not required)
Experience with
- No coding, programming, or terminal experience is needed. This course is designed for individuals who have never written code.
- No prior experience with Claude or any other AI tool is necessary.
Technical requirements
- Participants should 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 will be sent prior to 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 (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 want to build prototypes without hiring developers.
- Educators and researchers exploring AI-assisted workflows.
- Anyone curious about Claude's capabilities 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
