Generative AI & LLM Engineering with RAG Systems

⏱ Duration & Time: 40 hrs (Mo - Fr, 9:30AM - 5:30PM)

📅 Next Course Date: 14th September

👥 Participants: Approx. 15

🌐 Location: Remote (live online sessions with instructors)

🗣 Course Language: English

💳 Course Fee: €1,800 (Special Offer - €1,500)

🎓 Completion: Certificate of Completion (DeepStackAI)

💼 Future Job Opportunities: Generative AI Engineer, LLM Engineer, AI Application Developer, Machine Learning Engineer (NLP focus), AI Solutions Architect

Expected Salary: €85,000 – €120,000 per year

Course Overview

This course provides a comprehensive introduction to generative artificial intelligence and large language model (LLM) engineering, with a particular focus on Retrieval-Augmented Generation (RAG) systems. Participants will explore the design, development, and deployment of advanced AI applications that integrate LLMs with external data sources to produce accurate, context aware outputs.

The program combines theoretical foundations with practical implementation, enabling learners to build scalable AI systems used in real world applications such as chatbots, knowledge assistants, and enterprise AI solutions.

Who This Course Is For?

This course is intended for software engineers seeking to transition into generative AI and LLM development. It is also suitable for data scientists and machine learning engineers who want to expand their expertise in building advanced AI applications. Professionals interested in developing intelligent systems such as chatbots, AI assistants, and knowledge retrieval systems will find this course particularly valuable.

What You’ll Learn?

In this course, you will develop a strong foundation in generative artificial intelligence and large language models (LLMs). You will learn how to design, fine-tune, and deploy LLMs for real world applications. The course covers prompt engineering techniques, embeddings, and vector databases, as well as the architecture and implementation of Retrieval-Augmented Generation (RAG) systems.

You will also explore how to build end-to-end AI pipelines using modern frameworks, integrate external data sources for context aware responses, and evaluate model performance. Additionally, the course addresses practical challenges such as hallucination mitigation, guardrails, and deploying scalable, production ready LLM applications.

A quick overview of all content

Starting dates: Generative AI & LLM Engineering with RAG Systems

14th Sep - 18th Sep

7th Dec - 11th Dec