Course Outline
Phase 1 — Meet Claude Code — 30 minutes
- Overview of Claude and what distinguishes Claude Code from standard chat
- Quick orientation: using the Claude app today (web or desktop); the CLI and other interfaces are covered in the reference card
- Interface tour: starting a coding session and understanding the workspace
- How Claude Code approaches tasks: 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: e.g., "make the header bigger," "change the color scheme," "add a navigation bar"
- Guided exercise: participants start a session and build a personalized "About Me" webpage, refining it through follow-up instructions
Goal: ensuring everyone passes the initial interaction hurdle and becomes comfortable with the interface.
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Break — 7 minutes |
Phase 2 — Building Real Things with Plain English — 55 minutes
Three progressively complex tasks performed using only natural language prompts.
- Task 1 — Interactive dashboard: Creating a styled dashboard with sample data, charts, and statistics. Practice providing design directions: "use a dark theme," "add a sidebar," "make it responsive."
- Task 2 — Data analysis: Providing a sample CSV file, asking 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: Building 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 behind-the-scenes actions: files created, code written, and how to interpret the output. Participants document their most effective prompts in a shared Prompt Playbook.
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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 on the same task
- Iterating and refining: asking Claude to explain choices, undo changes, or try alternative approaches
- Working with uploaded files: e.g., "read this document and summarize it," "convert this spreadsheet into a chart"
- Multi-step workflows: chaining requests to build complex outputs
- Understanding cost and usage: how tokens, context windows, and subscription tiers function
- 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: elevating skills from "it works" to "I can get great results consistently."
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Break — 7 minutes |
Phase 4 — Connecting Claude to Your Tools with MCP — 34 minutes
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Pre-class: participants received email instructions to connect Gmail or Google Drive before the session, so classroom time is focused on using the connection rather than authenticating. |
- 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 assign a task to Claude — 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: helping 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 they connected in Phase 4, transform it, and produce a deliverable
The instructor circulates, helps refine prompts, and showcases standout examples.
Wrap-up (10 min):
- Next steps: Claude Code CLI for terminal users, VS Code extension for developers, and Cowork for knowledge workers
- Subscription plans: Free vs. Pro vs. Max — what each unlocks and which fits which use case
- Recommended resources: official docs, Anthropic’s prompt engineering guide, and community channels
- Participants leave with a reference card covering prompting patterns, connector setup, and 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 assistants' functions (e.g., casual experience with ChatGPT, Gemini, or Claude is beneficial context, though not mandatory)
Experience Level
- No coding, programming, or terminal experience is required. This course is specifically designed for individuals who have never written a line of code.
- No prior experience with Claude or any other AI tools is necessary.
Technical Requirements
- Participants must 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 registration; setup instructions are provided prior to the class)
- 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), though 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 a developer
- 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
