Course Outline
Phase 1 — Introduction to Claude Code — 30 minutes
- Overview of Claude and the distinctions between Claude Code and standard chat interfaces
- Quick orientation: focus on the Claude app (web or desktop) for today’s session; CLI and other interfaces are detailed in the reference card
- Interface walkthrough: initiating a coding session and familiarizing oneself with the workspace
- Claude Code’s logic: the describe → plan → act → review cycle
- Permissions: understanding why Claude requests confirmation before creating files or executing code
- First build: directing Claude to create a simple styled webpage from a one-sentence description
- Refining results: issuing commands like “make the header bigger,” “adjust the color scheme,” or “add a navigation bar”
- Guided exercise: participants begin a session and build a personalized “About Me” webpage, refining it through follow-up instructions
Objective: Overcome initial hurdles and become comfortable with the interface.
Break — 7 minutes
Phase 2 — Creating Real Applications with Plain English — 55 minutes
Three tasks of increasing complexity using only natural language prompts.
- Task 1 — Interactive dashboard: Design a styled dashboard with sample data, charts, and statistics. Practice giving design direction such as “use a dark theme,” “add a sidebar,” or “make it responsive.”
- Task 2 — Data analysis: Provide a sample CSV file and ask Claude to summarize it, identify trends, locate highs/lows, and generate a visual chart. This demonstrates Claude writing and executing code on your behalf.
- Task 3 — Automation tool: Develop 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 explains the background actions: files created, code written, and how to interpret the output. Participants record their best prompts in a shared Prompt Playbook.
Break — 7 minutes
Phase 3 — Advanced Techniques with Claude Code — 35 minutes
- The art of effective prompting: specific versus vague instructions
- Live demonstration: side-by-side comparison of weak and strong prompts applied to the same task
- Iteration and refinement: asking Claude to explain choices, revert changes, or try alternative approaches
- Handling uploaded files: requests such as “read this document and summarize it” or “convert this spreadsheet into a chart”
- Multi-step workflows: chaining requests to create complex outputs
- Cost and usage: understanding tokens, context windows, and subscription tiers
- Determining when to use Claude Code versus standard Claude chat
- Guided exercise: participants enhance a Phase 2 project with a new feature using a multi-step prompt, then compare the before-and-after prompts to identify key differences
Objective: Progress from basic functionality to consistently achieving high-quality results.
Break — 7 minutes
Phase 4 — Integrating Claude with Your Tools via MCP — 34 minutes
Pre-class: Participants received email instructions to connect Gmail or Google Drive prior to the session, allowing classroom time to focus on using the connection rather than authentication.
- Overview of MCP (Model Context Protocol): The universal interface for AI tools
- The importance of MCP: transforming Claude from a chat assistant into a connected workflow hub
- Connectors Directory: browsing and adding integrations directly from the Claude app
- Desktop Extensions: one-click installations (for Claude Desktop users)
- Live demonstration (single workflow): “Check my Google Calendar for tomorrow’s meetings and draft a preparation 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 locating new connectors
Objective: View Claude as a connective layer, not just a coding tool.
Phase 5 — Capstone & Conclusion — 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, and produce a visual report
- An interactive tool solving a real problem within their workflow
- A connected workflow: pull data from the service connected in Phase 4, transform it, and produce a deliverable
The instructor circulates to assist with prompt refinement and highlights standout examples.
Conclusion (10 min):
- Next steps: Claude Code CLI for terminal users, VS Code extension for developers, and Cowork for knowledge workers
- Plans: Free vs. Pro vs. Max — details on what each tier unlocks and the best use cases
- Recommended resources: official documentation, Anthropic’s prompt engineering guide, and community channels
- Participants leave with a reference card covering prompting patterns, connector setup, and useful MCP integrations
Requirements
Prerequisites
Basic Understanding
- Essential computer literacy: managing files and folders, navigating a web browser, and installing applications
- General familiarity with AI assistants (previous casual use of ChatGPT, Gemini, or Claude provides helpful context, though it is not mandatory)
Experience
- No coding, programming, or terminal experience is necessary. This course is tailored for individuals who have never written code.
- No prior experience with Claude or other AI tools is required.
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 duration of the session (a 1-month complimentary subscription is included with registration; setup instructions are sent 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 (covering Gmail, Google Drive, and Google Calendar), although alternative connector options are available
Target Audience
- Business professionals seeking to enhance productivity and automation through AI
- Marketing specialists, 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
- Individuals curious about Claude’s capabilities who lack 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
