💡 Summary
A course designed to help leaders build AI workflows and agents without prior coding experience.
🎯 Target Audience
🤖 AI Roast: “This course promises to turn you into an AI wizard, but don't forget your magic wand—aka a decent code editor.”
The course relies on external AI APIs, which may expose sensitive data if not handled properly. Ensure API keys are stored securely and not hardcoded in scripts.
🚀 Hands-on AI for Leaders
Build AI workflows and agents that automate workflow bottlenecks and save 10+ hours/week
This repository contains the source code, prompts, and examples for the Hands-on AI for Leaders course - a practical 4-week program designed to help leaders master AI tools and build autonomous systems without prior coding experience.
📚 About the Course
Instructor: James Gray - Former Microsoft Data Scientist & Berkeley Haas AI Strategy Instructor
What You'll Learn:
- 🤖 Master AI assistants to boost productivity
- 🔄 Build AI workflows that automate repetitive work
- 🧠 Create multi-agent systems for autonomous outcomes
- 💻 Use AI for code generation (no coding experience required)
- 📊 Strengthen technical expertise to lead AI initiatives
🗂️ Repository Structure
This companion repository provides all the code examples, templates, and resources you'll need throughout the course:
Week 1 - AI Assistant Foundations
Focus: Master prompt engineering and AI assistant capabilities
- Prompt templates and patterns
- Style guides and audience customization
- Real-world assistant examples
Week 2 - AI Workflows with Assistants and No-Code Platforms
Focus: Build automated workflows without writing code
- Marketing campaign automation
- No-code platform integrations
- Assistant-based workflow design
Week 3 - AI Workflows with Code and Agent Foundations
Focus: Leverage AI to write code and build advanced workflows
- API integrations (OpenAI, Anthropic, Google, Perplexity)
- Custom functions and tools
- Web search and file processing capabilities
- Model Context Protocol (MCP) implementations
Week 4 - Multi-Agent Systems
Focus: Design and deploy autonomous agent systems
- Single-agent implementations
- Multi-agent architectures (handoff, deterministic, agent-as-tool patterns)
- Production-ready agent deployments
🛠️ Getting Started
Prerequisites
- No coding experience required (AI will help you write code!)
- Python 3.11+ (for Week 3 & 4 exercises)
- An AI-powered code editor (setup guide)
📖 How to Use This Repository
- Week 1-2: Browse the prompt templates and workflow examples
- Week 3: Run the Python scripts to understand API integrations
- Week 4: Build and customize your own agent systems
Each week's folder contains:
- 📝 Markdown files with instructions and templates
- 🐍 Python scripts with working examples
- 📁 Output folders showing sample results
🎯 Course Enrollment
Ready to transform how you work with AI? Enroll in the full course to get:
- Live instruction and Q&A sessions
- Access to the course community
- Lifetime updates to course content
- Personalized feedback on your AI implementations
🤝 Support
- Course Support: Available through the Maven platform for enrolled students
- Technical Issues: Create an issue in this repository
- General Questions: Connect with the course community on Slack
📄 License
This repository is provided as a learning resource for course participants.
Pros
- No coding experience required
- Practical, hands-on learning approach
- Covers a wide range of AI applications
- Access to community support
Cons
- Requires Python installation
- Limited to course participants
- May not cover advanced AI topics
- Dependency on external AI tools
Related Skills
pytorch
S“It's the Swiss Army knife of deep learning, but good luck figuring out which of the 47 installation methods is the one that won't break your system.”
agno
S“It promises to be the Kubernetes for agents, but let's see if developers have the patience to learn yet another orchestration layer.”
nuxt-skills
S“It's essentially a well-organized cheat sheet that turns your AI assistant into a Nuxt framework parrot.”
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author jamesgray007.