Course Outline
Phase 1 — Meet Claude Code — 30 minutes
- Understanding what Claude is and how Claude Code differs from standard chat
- Quick orientation: today we use the Claude app (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 create a simple styled webpage from a one-sentence description
- Iterating on results: “make the header bigger,” “change the colour scheme,” “add a navigation bar”
- Guided exercise: participants initiate a session and build a personalised “About Me” webpage, refining it through follow-up instructions
Goal: everyone overcomes the first-interaction hurdle and feels comfortable with the interface.
Break — 7 minutes
Phase 2 — Building Real Things with Plain English — 55 minutes
Three progressively complex tasks utilising 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 summarise it, identify trends, find highs/low values, and generate a visual chart. This demonstrates Claude writing and executing code on your behalf.
- Task 3 — Automation tool: construct 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 highlights what happened behind the scenes: 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: specific versus vague instructions
- Live demo: side-by-side comparison of weak and strong prompts for the same task
- Iterating and refining: asking Claude to explain choices, undo changes, or attempt a different approach
- Working with uploaded files: “read this document and summarise it,” “convert this spreadsheet into a chart”
- Multi-step workflows: chaining requests to construct 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 drove the difference
Goal: elevate from “it works” to “I can consistently achieve great results.”
Break — 7 minutes
Phase 4 — Connecting Claude to Your Tools with MCP — 34 minutes
Pre-class: participants received emailed instructions to connect Gmail or Google Drive prior to the session, ensuring classroom time focuses 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 give 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 where to find 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, analyse 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
The instructor circulates, assists with refining prompts, and showcases standout examples.
Wrap-up (10 min):
- Where to go from here: 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 depart 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' functions (e.g., casual usage of ChatGPT, Gemini, or Claude is beneficial context but not mandatory)
Experience with
- No coding, programming, or terminal experience is required. This course is tailored for individuals who have never written a line of code.
- No prior familiarity 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 gift subscription is included with course registration; setup instructions are sent prior to class)
- Claude Desktop is recommended but not mandatory (the web app at claude.ai is sufficient for all exercises)
- A Google account is advisable 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 wishing to build prototypes without engaging 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
