Course Outline
Phase 1 — Introduction to Claude Code — 30 minutes
- Defining Claude and distinguishing Claude Code from standard chat interfaces
- Quick orientation: Using the Claude app (web or desktop); CLI and other interfaces are detailed in the reference card
- Interface overview: Initiating a coding session and navigating the workspace
- Understanding Claude Code’s logic: The describe → plan → act → review cycle
- Permissions explanation: Why Claude seeks confirmation before creating files or executing code
- First build: Instructing Claude to generate a simple styled webpage from a single-sentence description
- Refining results: Commands such as "make the header bigger," "change the color scheme," or "add a navigation bar"
- Guided exercise: Participants initiate a session and create a personalized "About Me" webpage, refining it through iterative instructions
Objective: Overcome initial hesitation and gain comfort with the interface.
Break — 7 minutes
Phase 2 — Creating Real Solutions with Plain English — 55 minutes
Three tasks of increasing complexity, completed solely using natural language prompts.
- Task 1 — Interactive dashboard: Create a styled dashboard with sample data, charts, and stats. Practice design directives like "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 data, identify trends, find peaks and lows, and generate visual charts. This demonstrates Claude writing and executing code on the user's behalf.
- Task 3 — Automation tool: Develop a simple utility such as a unit converter, quiz app, or budget calculator. This introduces the concept of Claude building interactive tools, not just static pages.
Following each task, the instructor explains the background processes: files created, code generated, and how to interpret the output. Participants document their most effective prompts in a shared Prompt Playbook.
Break — 7 minutes
Phase 3 — Optimizing Interactions with Claude Code — 35 minutes
- Mastering effective prompting: Specific vs. vague instructions
- Live demonstration: Side-by-side comparison of weak vs. strong prompts for identical tasks
- Iteration and refinement: Asking Claude to explain decisions, revert changes, or try alternative approaches
- Utilizing uploaded files: Commands like "read this document and summarize it" or "convert this spreadsheet into a chart"
- Multi-step workflows: Chaining requests to produce complex outputs
- Cost and usage insights: Understanding tokens, context windows, and subscription tiers
- Decision guide: When to use Claude Code vs. standard Claude chat
- Guided exercise: Participants extend a Phase 2 project by adding a new feature via a multi-step prompt, then compare prompt versions to identify key differences
Objective: Progress from "it works" to "I can consistently achieve excellent results."
Break — 7 minutes
Phase 4 — Integrating Claude with Your Tools via MCP — 34 minutes
Pre-class preparation: Participants receive instructions via email to connect Gmail or Google Drive before the session, allowing class time to focus on usage rather than authentication.
- MCP (Model Context Protocol) explained: The universal integration standard for AI tools
- The value of MCP: 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 installation options (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 a pre-connected service (or connect one live) to assign a task to Claude, such as "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 Project & 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 that solves a specific problem in their workflow
- A connected workflow: Retrieve data from the service connected in Phase 4, transform it, and generate a deliverable
The instructor circulates the room to assist with prompt refinement and highlight 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 — features unlocked and appropriate use cases
- Recommended resources: Official documentation, Anthropic’s prompt engineering guide, and community channels
- Takeaways: Participants leave with a reference card covering prompting patterns, connector setup, and useful MCP integrations
Requirements
Prerequisites
Basic Knowledge of
- Essential computer literacy: managing files and folders, using web browsers, and installing software
- General familiarity with AI assistants (previous casual use of ChatGPT, Gemini, or Claude is beneficial but not mandatory)
Experience Level
- No coding, programming, or terminal experience is necessary. This course is tailored for individuals who have never written code.
- Prior experience with Claude or other AI tools is not a requirement.
Technical Setup
- 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 one-month complimentary subscription is included upon registration; setup instructions are provided prior to the class)
- Claude Desktop is suggested but not mandatory (the web interface at claude.ai supports all exercises)
- A Google account is recommended for MCP connector exercises (Gmail, Google Drive, Google Calendar), though alternative connector options are available
Target Audience
- Business professionals seeking to enhance productivity and automation through AI
- Marketing, operations, and analysis teams aiming to streamline repetitive tasks
- Founders and entrepreneurs looking to create prototypes without hiring a developer
- Educators and researchers exploring AI-integrated workflows
- Anyone interested in what Claude can build, regardless of technical background
Testimonials (2)
The session was highly interactive and applicable to the business.
Jorge Boscan - Chevron Global Technology Services Company
Course - Advanced GitHub Copilot & AI for Projects and Infrastructure
Machine Translated
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
