ZeroToMastery – AI Engineering: Fine-Tuning LLMs 2025-7
ZeroToMastery – AI Engineering: Fine-Tuning LLMs 2025-7 Downloadly IRSpace
AI Engineering: Fine-Tuning LLMs is a course on the practical and theoretical aspects of customizing large language models (LLMs) published by ZeroToMastery Online Academy. This is an advanced course that focuses on the practical and theoretical aspects of customizing large language models (LLMs) for specific use cases. This course is designed for developers, data scientists, and AI enthusiasts who want to gain hands-on experience in fine-tuning, optimizing, and efficiently deploying LLMs in real-world environments. There’s no obscure theory here. Just modern, practical AI engineering skills that you can use right away.
If you’re interested in AI that actually does things—not just talking about it—this short course is for you. Whether you’re building smarter chatbots, personalized learning systems, or custom content generators, this course gives you the tools to do just that by fine-tuning your own custom AI model. You’ll learn how to prepare data, structure your training workflow, and evaluate your results like a pro.
What you will learn in AI Engineering: Fine-Tuning LLMs:
- Customizing LLMs for Your Purposes, Whether You’re in Finance, Law, Technology, or Anything Else
- How to Prepare Datasets for LLM Fine-Tuning
- The Process of Training GPT Models and How They Learn
- Fine-Tuning GPT Models Using the OpenAI API
- Rapid Engineering vs. Fine-Tuning: When to Use Each
- Creating Targeted, Personalized Outputs from GPTs
- And…
Course specifications
Publisher: ZeroToMastery
Instructors: Diogo Resende
Language: English
Level: Introductory to Advanced
Number of Lessons: 14
Duration: 1 hours and 35 minutes
Course topics

AI Engineering: Fine-Tuning LLMs Prerequisites
A computer with an internet connection
Basic Python knowledge
Pictures

AI Engineering: Fine-Tuning LLMs introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Download link
Size
303 MB
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