LLMs Engineering : From Using LLMs to Training LLMs

Description

This is a complete course that will prepare you to use Large Language Model. We will cover the fundamentals of Large Language Model with the main purpose of applying LLMs in real world applications, this course is structured on a 6 levels in which we will start learning LLM starting from the basic concepts of LLM and them grow little by little from closed paid models to build our chatbot and then add your own data to the model to generate a more suitable replies, after that we grow to apply open source models  in your work, after that we get to the level to fine tune an already existing model to apply to our application, after that we got to the point to train the model from scratch using PyTorch.

What Skills will you Learn:

In this course, you will learn the following skills:

• Understand the Math behind NLP Language Algorithms.

• Understand the Math behind LLMs Language Algorithms.

• Write and build Machine Learning/ LLM Algorithms.

• Apply LLMs using paid Closed models (ChatGPT and DeepSeek).

• Apply LLMs using Open source models.

• Fine Tune Already existing Models.

• Train LLMs from Scratch using PyTorch.

• Use opensource libraries related to LLMs, such as OpenAI, Hugging Face, and LangChain.

  
  

We will cover:

• Introduction Fundamentals of NLP (Natural Language Processing) and LLM (Large Language Model).

• Level 1 : Prompt Engineering using Closed Source Models

• Level 2 : RAG (Retrieval-Augmented Generation) Model using closed Source Models

• Level 3 : Prompt Engineering using OPEN Source Models

• Level 4 : RAG (Retrieval-Augmented Generation) Model using OPEN Source Models

• Level 5 : Model Fine Tuning

• Level 6 :Train Your LLM from scratch to write a novel.

If you do not have prior experience in Machine Learning OR Natural Language Processing (NLP) OR Large Language Model (LLM ), that's NO PROBLEM!. This course is complete and concise, covering the fundamentals of  NLP and LLM Engineering.