Advanced LLMs is a hands-on programme designed specifically for Data Science practitioners who want to expand their machine learning knowledge into Large Language Models.

The programme provides a practical, working-level understanding of the modern LLMs lifecycle. Instead of focusing on one area in depth, you’ll explore the key concepts, tools, and workflows involved in developing, adapting, deploying, and governing LLM-powered applications.

Throughout the programme, you’ll learn how to:

• Understand how Large Language Models work
• Apply advanced prompt engineering techniques
• Fine-tune pre-trained models for specific use cases
• Manage machine learning workflows with MLOps
• Deploy machine learning models through APIs
• Explore agentic AI concepts using LangChain and MCP
• Evaluate AI systems using responsible AI and governance principles

You’ll also complete practical labs and a capstone project that brings these concepts together in a real-world application.

This programme is designed for Data Science practitioners who already have a foundation in Python and machine learning and want to build practical skills in Large Language Models.

It is ideal for:

• Moringa School Data Science alumni looking to extend their skills into LLMs
• Data Scientists who want to understand how LLMs complement traditional machine learning
• Machine Learning practitioners interested in modern AI workflows
• Data professionals looking to apply LLMs within their organizations
• Technical professionals with a data science background who meet the programme prerequisites

If you’re unsure whether you’re ready, our admissions team can help assess your technical background and recommend the right learning path.

• Proficiency in Python (functions, libraries, data manipulation).
• Foundational understanding of machine learning concepts (supervised learning, model evaluation).
• Familiarity with data science workflows and tools (e.g., Pandas, Jupyter Notebooks).
• Basic understanding of APIs and version control (Git).

Large Language Models are becoming an important part of modern data science. Organizations increasingly expect data professionals to understand how these models are adapted, evaluated, and deployed, not just how to use AI tools.

Over seven weeks, you’ll gain practical experience across the modern LLMs lifecycle, including:

• Understanding transformer-based models and inference
• Designing effective prompts for different business and technical scenarios
• Fine-tuning pre-trained models using curated datasets
• Managing experiments with MLflow and MLOps workflows
• Deploying machine learning models using Flask APIs
• Exploring agentic AI with LangChain and Model Context Protocol (MCP)
• Applying responsible AI and governance principles to real-world deployments

By the end of the programme, you’ll have a practical understanding of how LLM-powered applications are developed and deployed, along with a portfolio project that demonstrates your learning.

• Applied, Hands-On Learning: We don’t just teach concepts. You will build, fine-tune, and deploy real AI systems through daily labs and practical projects.
• Open-Source MLOps Stack: Master the exact industry-standard frameworks (Hugging Face, MLflow, LangChain, Flask) used by leading engineering teams.
• Expert Guidance: Learn from instructors with real-world experience deploying AI systems in enterprise environments.
• Accredited Excellence: Benefit from Moringa’s TVETA-accredited curriculum and join a powerful network of tech professionals across Africa.