Udemy – AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents 2026-6

7 Jul at 3:46 am

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Description

AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents is a training course on working with large language models (LLM) published by Udemy Online Academy. AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents is a comprehensive course designed to equip developers with the knowledge and skills to work with large language models (LLMs) such as GPT-3 and GPT-4. This course covers the fundamentals of LLMs, how they are taught, and their applications in Natural Language Processing (NLP). Individuals learn how to fine-tune, deploy, and integrate LLMs into real-world applications such as chatbots, automated content generation, and sentiment analysis. Through hands-on projects, learners will gain hands-on experience in teaching LLMs, optimizing their performance, and managing AI-based workflows.

This course covers the basics of large language models, their training, and their applications to NLP tasks. Learners will gain hands-on experience in fine-tuning, deploying and integrating the LLM for projects such as chatbots and content creation, while also exploring ethical challenges and optimizing AI performance for real-world solutions. This course also examines ethical considerations and challenges in working with artificial intelligence systems. At the end, individuals will have the expertise to build, deploy and scale artificial intelligence solutions using LLM technology.

What you will learn in AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents:

Comparison of the latest techniques to improve the performance of the LLM solution
Using open source platforms, frameworks and tools, including Hugging Face, Gradio and Weights & Biases
Fundamental concepts of data science about deep learning
Common paradigms of artificial intelligence
Core concepts such as generative artificial intelligence
Implementation of LLM solutions in Python using boundary models and open source with both API and direct inference
and…

Course specifications

Publisher : Udemy
Teacher : Ligency , Ed Donner
Language: English
Level : All Levels
Lectures : 210
Duration : 33 hours and 27 minutes

Course topics

AI Engineer Core Track_ LLM Engineering, RAG, QLoRA, Agents

AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents Prerequisites

Familiarity with Python. This course will not cover Python basics and is completed in Python.

Pictures

Deep Learning A-Z [2026]_ DL, AI in Python & AWS + LLM Prize

AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents introduction video

Installation guide

After Extract, watch with your favorite Player.

Subtitle: English

Quality: 1080p

Previous Title:

LLM Engineering: Master AI & Large Language Models (LLMs)

Changes:

The 2025/12 version has increased the number of lessons by 27 and the duration increased by 4 hours 46 minutes compared to 2025/11.

The 2025/12 version has increased the number of lessons by 44 and the duration increased by 7 hours 3 minutes compared to 2025/12.

The 2026/1 version has decreased the number of lessons by 224 and the duration decreased by 25 hours 8 minutes compared to 2025/12.

The 2026/2 version has not changed in regards of lectures compared to 2026/1.

The 2026/6 version has increased the number of lessons by 2 and the duration increased by 4 minutes compared to 2026/2.

Download link

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Download Part 5 – 4 GB

Download Part 6 – 3.23 GB

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