MENA AI and Data Community

#2 of 3 Masterclasses: RAG Pipeline Engineering with LlamaIndex & Pinecone

This is the second masterclass in our 3-part AI Accelerator Bootcamp series, focused on helping participants move from AI concepts to practical AI application building.
In this session, we will go deeper into RAG Pipeline Engineering and understand how modern AI applications retrieve, process, and generate responses using company or domain-specific data.
You will learn how to structure a practical RAG workflow using LlamaIndex for orchestration and Pinecone as a vector database for storing and retrieving embeddings.
Session Details
Topic: RAG Pipeline Engineering with LlamaIndex & Pinecone
Part: Masterclass 2 of 3
Date: Saturday, 25th July
Time: 11:00 AM. GST
Program: AI Accelerator Bootcamp
Certification: CPD UK Certified Bootcamp
CPD Hours: Part of the 10 CPD hours bootcamp certification
What we will cover

• How a RAG pipeline works from documents to final LLM response
• How to prepare and structure data sources
• Chunking and indexing strategies for real-world applications
• Using LlamaIndex to orchestrate retrieval logic
• Using Pinecone as a vector database for semantic search
• How retrieval connects with LLM responses
• Practical design principles for building scalable RAG applications

This masterclass is ideal for learners, developers, data professionals, and AI enthusiasts who want to understand how to build AI applications that can work with real documents, business knowledge, and private datasets.

By the end of the session, participants will have a clearer understanding of how RAG systems are engineered and how tools like LlamaIndex and Pinecone fit into the AI application development workflow.

MC03: GROQ and Building Apps with APIs in Python (1st Project)

Take the next step in your AI development journey by learning how to build intelligent applications powered by APIs and high-speed inference with GROQ.

In this masterclass, you'll explore how to integrate AI models into Python applications using APIs, understand the fundamentals of API communication, and build your first end-to-end AI project. Through hands-on exercises, you'll gain practical experience connecting external AI services, processing user inputs, and generating intelligent outputs.

Key Learning Outcomes:

• Understand how APIs enable AI-powered applications.
• Learn to integrate GROQ's high-speed inference platform with Python.
• Send API requests and process AI-generated responses.
• Build your first AI-powered Python application from scratch.
• Apply best practices for working with API keys, requests, and responses.

By the end of this session, you'll have completed your first functional AI project and gained the foundational skills needed to build more advanced AI applications.

MC16: Multi-AI Agent Systems with CrewAI is an advanced, hands-on masterclass under the AI Residency program focused on building collaborative AI systems powered by multiple intelligent agents.

In this session, participants will learn how to design, orchestrate, and manage multi-agent workflows using CrewAI. The masterclass covers agent roles, task delegation, collaboration strategies, memory, and tool integration—enabling AI agents to work together toward complex goals. By the end of the session, learners will be equipped to build autonomous, scalable, and highly efficient multi-agent systems for real-world business and enterprise applications.
This masterclass is part of the AI Residency.