Kubrick Course

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Hi Dave...

Learn to build AI Agents that can understand images, text, audio and videos.

A free, Open-source course by The Neural Maze and Neural Bits in collaboration with Pixeltable and Opik

📖 About This Course

Tired of tutorials that just walk you through connecting an existing MCP server to Claude Desktop?

Yeah, us too.

That's why we built Kubrick AI, an MCP Multimodal Agent for video processing tasks. Yes! You read that right. Agents + Video Processing ... and MCP!

This course, is a collaboration between The Neural Maze and Neural Bits (from now on, "The Neural Bros"), and it's built for developers who want to go beyond the basics and build serious, production-ready AI Systems. In particular, you'll:

Learn how to build an MCP server for video processing using Pixeltable and FastMCP
Design a custom, Groq-powered agent, connected to your MCP server with its own MCP client
Integrate your agentic system with Opik for full observability and prompt versioning

🖊️ What you'll learn

Learn how to use Pixeltable for multimodal data processing and stateful agents
Create complex MCP servers using FastMCP: expose resources, prompts and tools
Apply prompt versioning to your MCP server (instead of defining the prompts in the Agent API)
Learn how to implement custom MCP clients for your agents
Implement an MCP Tool Agent from scratch, using Llama 4 Scout and Maverick as the LLMs
Use Opik for MCP prompt versioning
Learn how to implement custom tracing and monitoring with Opik

No shortcuts. No fluff. Let's learn by doing.

💻 What You'll Do:

Completing this course, you'll learn how to design and enable Agents to understand multimodal data, across images, video, audio and text inputs all within a single system.

Specifically, you'll get to:

Build a complex Multimodal Processing Pipeline
Build a Video Search Engine and expose its functionality to an Agent via MCP (Model Context Protocol)
Build a production ready API to power the Agent.
Integrate LLMOps principles and best software engineering practices.
Learn about video, embeddings, streaming APIs, Vision Language Models (VLMs) and more.

After completing this course, you'll have built your own Kubrick Agent with a HAL themed spin-off, to play the role of a new set of eyes and ears:

Publication	Description	Subscribe
Neural Bits	Learn about industry standards and production-ready AI Engineering.
The Neural Maze	Learn to build AI Systems that actually work, from principles to production. Delivered every Wednesday.

🧑‍🎓 Who is this course for?

You'll get the most of this course by building it yourself, from the ground up. The course components are structured to cover key concepts, and showcase how to build on top of them, towards AI Systems.

Target Audience	Skills you'll get
ML/AI Engineers	Build complex MCP Servers, learn to apply AI Models to Video, Images and Speech.
Software Engineers	Learn to connect AI Components with APIs, building end-to-end agentic applications.
Data Engineers/Scientists	Learn to design an AI System, managing Video/Audio/Image data processing and structure.

Regardless of your experience or title, this course aims to unpack complex topics in practical terms and concepts you could understand, learn and apply - helping you to build a complete AI system.

🎓 Prerequisites

In this section, we outlined a few requirements and nice-to-haves to improve your learning experience while taking this course.

Category	Label	Description
Programming Skills (Beginner)	Requirement	Understanding of Programming in general, and the Python language syntax.
AI/ML Concepts (Beginner)	Nice to Have	Understanding the basic concepts behind AI, AI Models and AI Systems.
LLMs, MCP, Agents	Nice to Have	Perfect if you know about them, not a problem if you don't. We'll teach and explain it step by step.
Laptop/PC with any OS	Requirement	AI Models inference requires compute. To overcome that, we'll mainly use API based models.

The overall level of this course is Beginner/Intermediate, but don't worry. We'll aim to explain every component step by step designed for a larger audience.

💰 What's the cost?

This course and its materials are open-source and completely free, thanks to our sponsors, Pixeltable and Opik!

You'll be able to run Kubrick examples while staying at 0 cost. That's because we'll use OpenAI and Groq for our LLM and VLM calls, which offer freemium plans as such:

Provider	Free Credits
OpenAI	$5/month on sign-up
Groq	500,000 tokens / day

[!NOTE]
In this setup, for running the Kubrick Agent example - the freemium plans are enough.

📚 Course Syllabus

The Kubrick Agent open-source course consists of 5 comprehensive modules, going through concepts, system design, tooling and hands-on implementation.

To get the most out of this course, we recommend:

Clone this repository.
Follow the Get Started Sections of each module.
Read the module articles to understand each component.
Follow the Video Lessons for hands-on implementation.
Set up the code and run the project.

Module No.	Written Lesson (Link)	Description	Code
0		Short course introduction and overview. Outlining the basic components	N/A



Pixeltable is the only Python framework that provides incremental storage, transformation, indexing, and orchestration of your multimodal data.	Opik LLM Evaluation platform helps you build, evaluate, and optimize LLM systems that run better, faster, and cheaper

Contributors

_{Miguel Otero Pedrido}
_{AI / ML Engineer}

_{Alex Razvant}
_{AI / ML Engineer}

Publication	Description	Subscribe
Neural Bits	Learn about industry standards and production-ready AI Engineering.
The Neural Maze	Learn to build AI Systems that actually work, from principles to production. Delivered every Wednesday.

multimodal-agents-course