That's why we’re thrilled to announce the launch of our new AI Foundations collection, a comprehensive set of labs designed to empower you to navigate the fast-paced world of AI confidently.

This seven-part lab collection is your guided tour through the core components of modern AI implementation. We've crafted this collection for everyone, breaking down complex concepts into digestible, easy-to-understand labs.

Whether you're a seasoned tech professional or just starting your AI journey, this collection will provide you with a practical, hands-on understanding of how AI systems are built and how they work together to deliver powerful capabilities.

NOTE: These labs are only available for customers who haven’t opted out of AI-related content.

Why a new AI collection?

Our customers have asked for more in-depth AI content – a demand that mirrors the explosive growth of the AI market.

This new collection is our commitment to staying at the forefront of the industry and proactively addressing the needs of our community.

What you'll learn

The AI Foundations collection is a journey through the essential concepts of artificial intelligence. Each lab builds on the last, culminating in a holistic understanding of modern AI systems, with a special focus on agentic AI.

Here's a glimpse into what you'll discover:

• Episode 1: Artificial Intelligence (Theory): Dive into the fundamentals of AI, exploring what it is, how it works, and the distinctions between generative AI and AGI. It also discusses AI’s limitations and demystifies the "illusion of thinking".
• Episode 2: Core Components (Theory): Get acquainted with the building blocks of AI, including LLMs, embedding and diffusion models, RAG, MCP, and the exciting world of agentic AI. It also touches on crucial security considerations as AI transitions from "knowing" to "doing".
• Episode 3: Large Language Models (Theory): Explore the power of foundational models, the importance of fine-tuning, the role of system prompts, and security considerations such as exploitable vulnerabilities and data privacy.
• Episode 4: Retrieval Augmented Generation (RAG) (Practical): Take a deep dive into RAG, vector databases, embedding, and chunking. In this hands-on lab, you'll create a knowledge base, chunk a file, and query a fictional company's proprietary data through an integrated AI chatbot.
• Episode 5: Model Context Protocol (MCP) (Practical): Understand the MCP protocol and its architecture within the broader AI landscape. You'll get hands-on experience using MCP Inspector to interact with an MCP server, and instruct an AI chatbot to organize files on your desktop, gaining insight into exactly how tools are chosen and invoked.
• Episode 6: Agentic AI (Practical): Immerse yourself in the world of AI agents. You'll get access to real AI agents within a safe sandbox environment. The curious can poke and edit the code and explore integrated Langfuse for a deeper look into the observability of the AI system.
• Episode 7: Demonstrate Your Knowledge (Theory): Put your newfound knowledge to the test and solidify your understanding of the concepts covered throughout the collection.

Secure and private by design

We've built our practical AI labs with your security and privacy as the top priority.

When you launch a lab, you're entering a completely isolated, sandboxed environment. These sandboxes are self-contained and have no connection to any customer data or personal information. Think of it as your own private, temporary workspace that’s thoroughly purged after each use.

To interact with the AI models, each lab session creates temporary user credentials. Not only are these credentials temporary, but they’re also locked to the lab environment itself. This means that even if the credentials were to be exposed, they would be useless outside of the specific lab they were created for, providing a robust layer of security.

Access to the internet is also strictly controlled, which only allows connections to the minimum endpoints required for the lab to function.

We utilize privacy-centric AI models designed to protect your data. The models we use don’t store or log your prompts and completions. Furthermore, your interactions are never used to train any models, ensuring that your data remains your own. We’ve also opted out of any content being used for service improvements across all the AI services we use.

In some of our more advanced labs, we've implemented an additional layer of security with guardrails that preprocess user inputs and model outputs to filter for harmful or inappropriate content. These guardrails are mandatory and can’t be bypassed by users within the lab environment.

These multiple layers of security work together to provide a safe and secure environment for you to learn and experiment with AI.

Who is this collection for?

Everyone!

We've designed these labs to be a guided walkthrough, making even the more technical details accessible to anyone working with or interested in AI.

Whether you're a developer, a business leader, a student, or simply a curious mind, our AI Foundations course will equip you with the knowledge and skills to thrive in the age of artificial intelligence.

Join us on this exciting journey and unlock the power of AI. Get ready to build, innovate, and lead in the new era of intelligence.