We have designed a series of hands-on workshops to take you from zero to hero with Generative AI. Here's a list of workshops we currently have:
| Workshop name | Links | Description | Language | Tools used |
|---|---|---|---|---|
| AI System Design: From Problem to Production | Slides + Self-paced lab | Learn a structured framework for making the decisions that get your AI systems to production. Apply the framework to a real-world problem as you go, leaving with a concrete system design and a repeatable process for taking AI applications from problem to production. | ||
| Vector Search: Beginner to Pro | Slides + Self-paced lab | Learn vector search concepts such as embeddings, how vector search works in MongoDB, and also advanced concepts such as pre-filtering, vector quantization etc. Gain hands-on experience by building a multimodal vector search application for an online library. | Python | MongoDB Atlas, Voyage AI |
| Building RAG Applications with MongoDB | Slides + Self-paced lab | Learn RAG concepts such as embedding, chunking and vector search. Gain hands-on experience by building a RAG-based chatbot for a technical documentation website. | Python | MongoDB Atlas, Voyage AI, Anthropic/Azure OpenAI/Gemini |
| The A to Z of Building AI Agents | Slides + Self-paced lab | Learn the core concepts of AI agents, such as reasoning, tools, and memory. Gain hands-on experience by buiding a technical documentation AI agent. | Python | MongoDB Atlas, Voyage AI, Anthropic/Azure OpenAI/Gemini, LangGraph |
| Pragmatic LLM Application Development: From RAG Pipelines to AI Agents | Hands-on Lab | Build RAG pipelines and AI agents with and without abstraction frameworks such as LangChain. Also introduces techniques such as prompt compression for optimizing LLM apps. | Python | MongoDB Atlas, OpenAI, LangChain, LLMLingua |
| Building Multimodal AI Agents from Scratch | Video, Hands-on Lab | Learn techniques to process multimodal data and build a multimodal AI agent from scratch, no abstractions involved. | Python | Voyage AI, MongoDB Atlas, Gemini |
| Designing Memory Systems for AI Agents | Slides + Self-paced lab | Learn about the different types of memory in agentic systems, and patterns for storing, retrieving, updating and pruning memories. Gain hands-on experience by building a memory-augmented AI agent from scratch. | Python | Voyage AI, MongoDB |
Reach out to Apoorva Joshi