Course Outline
Phase 1 – Introduction to Claude Code – 30 minutes
- Understanding what Claude is and how Claude Code differs from standard chat interfaces
- Quick orientation: Using the Claude app today (web or desktop); CLI and other interfaces are detailed in the reference card
- Interface overview: initiating a coding session and navigating the workspace
- Claude Code’s thought process: the describe → plan → act → review loop
- Understanding permissions: why Claude requests confirmation before creating files or executing code
- Your first build: prompting Claude to generate a simple styled webpage from a brief description
- Iterating on results: commands like “make the header bigger,” “change the color scheme,” “add a navigation bar”
- Guided exercise: participants start a session and create a personalized “About Me” webpage, refining it through follow-up instructions
Goal: Overcome the initial interaction hurdle and become comfortable with the interface.
Break – 7 minutes
Phase 2 – Creating Practical Solutions with Natural Language – 55 minutes
Three progressively complex tasks completed 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 file, ask Claude to summarize findings, identify trends, locate 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 create interactive tools, not just static pages.
After each task, the instructor highlights Claude’s backend 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 – Optimizing Workflows 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 decisions, revert changes, or attempt different approaches
- Working with uploaded files: “Read this document and summarize it,” “Convert this spreadsheet into a chart”
- Multi-step workflows: Chaining requests to produce complex outputs
- Understanding costs and usage: How tokens, context windows, and subscription tiers function
- When to use Claude Code versus standard 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 key differences
Goal: Move from “it works” to “I can consistently achieve excellent results.”
Break – 7 minutes
Phase 4 – Connecting Claude to Your Tools via MCP – 34 minutes
Pre-class: Participants received email instructions to connect Gmail or Google Drive before the session, allowing classroom time to focus on usage 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, and locating new connectors
Goal: Participants view Claude as a connective layer, not merely 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, and 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
Instructor circulates to assist with prompt refinement 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
- Subscription 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
Prerequisites
Required Knowledge
- Fundamental computer skills: ability to navigate files and folders, use a web browser, and install software applications
- Basic familiarity with AI assistants (e.g., prior casual use of ChatGPT, Gemini, or Claude is beneficial but not mandatory)
Required Experience
- No coding, programming, or command-line terminal experience is needed. This course is specifically designed for individuals who have never written code.
- No previous experience with Claude or any other AI tool is necessary.
Technical Requirements
- A laptop (Mac, Windows, or Linux) equipped with a modern web browser
- Stable internet connectivity
- A Claude Pro subscription for the session (a 1-month complimentary subscription is provided upon registration; setup instructions will be sent prior to class)
- Claude Desktop is suggested but optional (the web app at claude.ai fully supports all exercises)
- A Google account is recommended for the MCP connectors exercise (for Gmail, Google Drive, and Google Calendar), though alternative connector options are available
Target Audience
- Business professionals seeking to enhance productivity and automation through AI
- 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
