Course Outline
Phase 1 — Meet Claude Code — 55 minutes
- An overview of what Claude is and how Claude Code differs from standard chat interfaces
- The Claude product family: claude.ai, Claude Desktop, Claude Code (CLI), and their relationships
- Interface tour: navigating the Claude app, initiating a coding session, and understanding the workspace
- Understanding Claude Code’s thought process: the describe → plan → act → review cycle
- Permissions explained: why Claude seeks approval before creating files or executing code
- Your first build: instructing Claude to create a simple styled webpage from a single-sentence description
- Iterating on results: “increase the header size,” “change the color scheme,” “add a navigation bar”
- Guided exercise: participants open the Claude app, start a Claude Code session, and build a personalized “About Me” webpage by describing their preferences in plain English. They practice refining outcomes through follow-up instructions.
Goal: everyone becomes comfortable with the interface and overcomes the initial interaction hurdle.
Break — 10 minutes
Phase 2 — Building Real Things with Plain English — 70 minutes
This forms the core of the morning session. Participants complete four progressively complex tasks using only natural language prompts.
- Task 1 — Interactive dashboard: instruct Claude Code to create a styled dashboard displaying sample data with charts, statistics, and a clean layout. Practice providing design direction: “apply a dark theme,” “add a sidebar,” “make it responsive.”
- Task 2 — Data analysis: provide Claude with a sample CSV file and ask it to summarize the data, identify trends, locate highest and lowest values, and generate a visual chart. This demonstrates how Claude writes and executes code on your behalf.
- Task 3 — Document generator: ask Claude to read a data file and produce a formatted report — such as a sales summary, project status update, or meeting recap. This shows how Claude transforms raw data into polished deliverables.
- Task 4 — Automation tool: ask Claude to create a simple utility — like 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 happens behind the scenes: which files are created, what code is generated, and how to interpret the output. Participants document their most effective prompts in a shared Prompt Playbook.
Break — 10 minutes
Phase 3 — Working Smarter with Claude Code — 50 minutes
- The art of effective prompting: balancing 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 its decisions, undo 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 generate complex outputs (“first analyze this data, then build a dashboard from the results”)
- Understanding cost and usage: how tokens, context windows, and subscription tiers operate
- Knowing when to use Claude Code versus regular Claude chat
- Guided exercise: participants take one of their Phase 2 projects and extend it with two new features using a multi-step prompt chain. They then compare their before-and-after prompts to identify what drove the improvement.
Goal: elevate your skills from “it works” to “I can consistently achieve great results.”
Break — 10 minutes
Phase 4 — Your Claude Workflows: Live Build Session — 60 minutes
This phase shifts the room’s energy. Instead of individual practice, the group builds together. While the instructor drives the process, participants call the shots — sharing real problems from their jobs, suggesting prompt ideas, and debating tradeoffs. The objective is to learn prompt judgment by observing how an expert navigates uncertainty in real time.
Three workflow archetypes structure the session:
- Transform — take input X, produce output Y (meeting notes → action items; raw data → summary email; customer feedback → themed report)
- Draft — generate a first version of content you would normally write from scratch (proposals, emails, job descriptions, social media posts)
- Analyze — interrogate a document or dataset you lack the time to review carefully (a 40-page report, a spreadsheet of survey responses, a contract)
Setup and framing (10 min): The instructor introduces the three archetypes and explains the session structure. Participants submit real workflow challenges from their jobs via a shared doc or chat.
Live build #1 — Transform workflow (20 min): The instructor selects one submitted problem, builds it live while the room suggests prompts, offers pushback, and refines ideas. The instructor narrates every decision. The session ends with a working prompt template that the participant who submitted the problem keeps.
Live build #2 — Draft or Analyze workflow (20 min): Same format, different archetype, and a different participant’s problem.
Reflection & share-back (10 min): Participants take a moment to jot down one prompting move that surprised them, one thing they would do differently, and one pattern they plan to adopt. A quick group share follows — featuring 3-4 voices, not everyone. The instructor connects observations to the broader Prompt Playbook.
Phase 5 — Connecting Claude to Your Tools with MCP — 50 minutes
- 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 (no configuration files required)
Live demo: The instructor links Claude to two services through the Connectors UI and demonstrates cross-tool workflows:
- “Check my Google Calendar for tomorrow’s meetings and draft a prep email for each one”
- “Read the latest updates from our project board and write a status summary”
- “Pull data from this connected service and build a local report from it”
Guided exercise: participants connect Claude to at least one service. Options are provided for varying comfort levels:
- Option A: Connect a pre-built connector from the directory (e.g., Gmail, Google Drive, or a demo service) — click, authenticate, and start
- Option B: Add a custom connector by pasting an MCP server URL (the instructor provides a test URL)
- Option C: Install a Desktop Extension from the marketplace (for Claude Desktop users)
Participants then task Claude with using the connected service — for example, “Read my recent emails about project updates and create a summary document.”
Key concepts covered:
- How connectors function: OAuth authentication, permissions, and the access you grant
- Managing tool access: enabling, disabling, and controlling which connectors Claude can use per conversation
- Security awareness: connecting only to trusted services and reviewing tool permissions
- The MCP ecosystem: where to find new connectors, extensions, and community-built servers
Goal: participants view Claude as a connective layer between all the services they already use, rather than just a coding tool.
Break — 10 minutes
Phase 6 — Capstone & Next Steps — 65 minutes
Capstone mini-project (45 min): Each participant selects one scenario and builds it with Claude:
- A polished landing page or portfolio site for their team, project, or personal brand
- A data analysis pipeline: upload a file, have Claude analyze it, and produce a visual report
- An interactive tool that solves a real problem from their workflow (calculator, tracker, converter, quiz)
- A connected workflow: pull data from a connected service, transform it, and produce a deliverable (e.g., “read my calendar for next week and build a visual schedule”)
The instructor circulates the room, helps refine prompts, and showcases standout examples to the group.
Showcase and wrap-up (20 min):
- 6-8 participants share what they built (2-3 minutes each)
- Where to go from here: Claude Code CLI for terminal users, VS Code extension for developers, Cowork for knowledge workers
- The MCP ecosystem: finding and evaluating new connectors, extensions, and community servers
- Plans: Free vs. Pro vs. Max — what each unlocks and which fits specific use cases
- Best practices recap: the Prompt Playbook patterns that worked best during the session
- Recommended resources: official documentation, community channels, Anthropic’s prompt engineering guide
- Participants receive a reference card containing key prompting patterns, connector setup steps, and a curated list of useful MCP integrations
Requirements
Prerequisites
You should have
- Basic computer literacy: ability to navigate files and folders, use a web browser, and install applications
- General awareness of AI assistant functions (e.g., having casually used ChatGPT, Gemini, or Claude provides helpful context but is not mandatory)
You do not need
- No coding, programming, or terminal experience is required. This course is tailored for individuals who have never written a line of code.
- No prior experience with Claude or any other 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 provided beforehand)
- Claude Desktop is recommended but not mandatory (the web app at claude.ai supports all exercises)
- A Google account is suggested for the MCP connectors exercise (Gmail, Google Drive, Google Calendar), though alternative connector options are available
Audience
- Business professionals aiming to leverage AI for productivity and automation
- Marketers, operations managers, and analysts seeking to automate repetitive tasks
- Founders and entrepreneurs interested in building prototypes without hiring 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
