Course Outline
Phase 1 — Meet Claude Code — 30 minutes
- Overview of Claude and what distinguishes Claude Code from standard chat
- Quick orientation: we are using the Claude app today (web or desktop); the CLI and other interfaces are covered in the reference card
- Interface tour: initiating a coding session and understanding the workspace
- Claude Code’s thought process: the describe → plan → act → review loop
- Understanding permissions: why Claude seeks approval before creating files or executing code
- Your first build: instructing Claude to generate a simple styled webpage from a one-sentence description
- Iterating on results: “make the header larger,” “change the color scheme,” “add a navigation bar”
- Guided exercise: participants initiate a session and build a personalized “About Me” webpage, refining it through follow-up instructions
Goal: everyone overcomes the initial interaction hurdle and becomes 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: 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 file, ask Claude to summarize the data, identify trends, locate highs/ lows, and generate a visual chart. This demonstrates Claude’s ability to write and execute 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 create interactive tools, not just static pages.
After each task, the instructor highlights Claude’s 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.
Break — 7 minutes
Phase 3 — Working Smarter with Claude Code — 35 minutes
- The art of effective prompting: distinguishing between specific and vague instructions
- Live demo: side-by-side comparison of weak versus strong prompts for the same task
- Iterating and refining: asking Claude to explain its choices, undo changes, or attempt 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
- Understanding cost and usage: how tokens, context windows, and subscription tiers operate
- 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: level up 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 instructions via email 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 assign 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, where to find new connectors
Goal: 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 selects 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 showcases 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 documentation, 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
- General awareness of AI assistants’ capabilities (e.g., having used ChatGPT, Gemini, or Claude casually provides helpful context but is not mandatory)
Experience with
- No coding, programming, or terminal experience is required. This course is tailored for individuals who have never written code.
- No prior experience with Claude or any AI tool is necessary.
Technical requirements
- Participants must 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 complimentary subscription is included with registration; setup instructions are provided prior to class)
- Claude Desktop is recommended but not mandatory (the web application at claude.ai suffices 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 seeking to leverage AI for productivity and automation
- Marketers, operations managers, and analysts aiming to automate repetitive tasks
- Founders and entrepreneurs interested in building 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
