Our Building Large Language Model Applications course is thoughtfully designed to provide you with foundational and advanced skills in Generative AI, LLM architecture, prompt engineering, fine-tuning, and deployment.

The focus will be on translating theoretical concepts into real-world applications, from creating effective prompts to deploying models on scalable platforms. Whether it’s crafting chatbots, optimizing semantic search, or training local LLMs, this course equips you with the tools to master the end-to-end lifecycle of Large Language Models.

This course is amongst the top-rated technical courses, and I am proud to say it's an extremely popular course.

The course is aimed to introduce you to Large Language Models in deeper detail on what transformer architecture is and how we utilize the Encoder and Decoder Models.

This is not a Langchain course but much more than that. We go into great depth to explain the building blocks of retrieval systems and how to utilize Open Source LLMs to build your RAG-based architectures.

Learning Outcome:

- Gain a comprehensive understanding of the end-to-end LLM architecture

- Construct and deploy robust and effective models in real-world settings using Large

Language Models. 

- Learn to tackle practical machine learning problems and deliver results in production.

Overall, students will emerge with greater confidence in their abilities to tackle practical machine learning problems and deliver results in production.

Please Note:

This is not a beginner course for non technical people, it requires knowledge of Python and some basic machine learning background.