Course Curriculum

    1. Welcome to the Course👋

    2. Let's Get To Know You📝

    1. Chapter Introduction⛷️

    2. AI Agents to Agentic AI🚀

    3. The Risk of Autonomous Agents⚠️

    4. Safety and Ethics with Agentic AI⚖️

    5. Chapter Quiz🧩

    6. Summary✅

    1. Chapter Introduction⛷️

    2. Setting Up Your AI Agent Lab🚧

    3. Microsoft Installation Guide🛠️

    4. MacOS Installation Guide🛠️

    5. Preparing Your Environment💻

    6. Chapter Quiz🧩

    7. Summary✅

    1. Chapter Introduction⛷️

    2. Running the Python Notebook🐍

    3. Bringing Your Agent to Life🌱

    4. Chapter Quiz🧩

    5. Summary✅

    1. Chapter Introduction⛷️

    2. Visualisation and Demo of the Agent👑

    3. Chapter Quiz🧩

    4. Summary✅

    1. You've Completed the Course!🎉

    2. Tell Us About Your Experience 🙏

About this course

  • Free
  • 26 lessons
  • + 2 Hours
  • Intermediate Level
  • Free Access until 3rd June

COURSE OVERVIEW

Tools You Need

  • Laptop/Computer
  • Browser with Internet Connection
  • Up to 600MB free storage
  • SciStarter Account
  • Ollama/Google Gemini account
  • VS Code

What You'll Learn

  • Understand how AI Agents work: Explain what AI agents are, how they make decisions, and how different components (like inputs, models, and outputs) work together.

  • Set up your own AI development environment: Install tools like Python, Jupyter Notebook, and required libraries to build and run your own AI projects.

  • Build a working AI Agent using Python: Create your own AI agent step-by-step, including handling user input, processing responses, and managing errors.

  • Apply AI responsibly and safely: Understand key ideas around AI ethics, trust, and safety - including how to design systems that are fair and reliable.

  • Launch a simple AI-powered app: Use tools like Streamlit to turn your AI agent into an interactive app that others can use.

Meet Your Instructors

Yu-Cheng Tsai

Principal Machine Learning Scientist, Sage

Yu-Cheng Tsai is a Ph.D. graduate from Princeton University in Mechanical and Aerospace Engineering, where he focused on computational physics. In 2021, he joined Sage AI to evaluate time-series models, develop production models for the invoice general ledger coding classification system, and prototype graph neural network models for accounting workflows and leveraging Generative AI.

Mac Chen

Machine Learning Engineer, Sage

Mac Chen is an engineer with an M.Sc. in Artificial Intelligence from the University of Edinburgh. In 2025, he joined Sage AI and focused on agentic LLM systems, developing reliable tool-calling and evaluation frameworks to measure correctness and robustness, and improving observability to make model behaviour auditable in production.

Bona Chow

Machine Learning Engineer, Sage

Bona holds an MSc in Natural Sciences from the University of Cambridge and began her career in gemmology. During the COVID-19 pandemic, she started learning how to code and studying Data Science in her spare time, quickly becoming fascinated by artificial intelligence and machine learning. Her dissertation project focused on developing a computer vision algorithm to classify 68 types of gemstones. She is passionate about using her experience to encourage more women and individuals from underrepresented backgrounds to explore opportunities in technology and pursue careers in AI.

Damani Eason

Senior Business Executive, Sage

Damani Eason is a Business Executive to the Chief Technology Officer at Sage. He holds a BSc in Industrial and Systems Engineering from the University of Florida. In his role, he partners with Sage’s AI, product, and engineering teams to shape how emerging technologies are translated into powerful solutions for businesses and developers. He is passionate about ensuring AI is accessible and resonates with the next generation, empowering them to move from using technology to building it.

CREATE SMART AI

Think Bigger. Act Responsibly.
What Will You Build?

The future won’t be shaped by passive users, it will be built by thoughtful creators.

In this course, you’ll learn how to build AI-powered projects and explore the world of agentic AI: systems that can take action, solve problems, and interact intelligently. But with great power comes responsibility. That’s why you’ll also learn how to design AI that is safe, ethical, and trustworthy.

Whether you're aiming for a future career, building your first project, or just curious about how AI really works, this course gives you the skills to stay ahead and build responsibly.

Take the Course

Frequently Asked Questions

  • What tools do I need to participate?

    You will need a good internet connection, a laptop/PC, a free Google account, and VS Code.

  • Do I have to already know coding?

    A basic knowledge of Python and how to use coding IDEs such as VS Code is essential to this course.

  • Can this help with future careers?

    Definitely - AI is one of the fastest-growing fields in the world. This course gives students early exposure to in-demand skills like coding, problem-solving, and working with AI systems.

  • Who should I contact if I have more questions?

    For more information, please contact Alanna at [email protected]

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