The demand for technical gen AI skills is exploding. Businesses are hunting hard for AI engineers who can work with large language models (LLMs). This Generative AI Engineering and Fine-Tuning Transformers course builds job-ready skills that will power your AI career forward.
Generative AI Engineering and Fine-Tuning Transformers
Generative AI Engineering and Fine-Tuning Transformers
This course is part of multiple programs.
Instructors: Joseph Santarcangelo
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4.4
(31 reviews)
Intermediate level
Recommended experience
8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Sought-after job-ready skills businesses need for working with transformer-based LLMs for generative AI engineering... in just 1 week.
How to perform parameter-efficient fine-tuning (PEFT) using LoRA and QLoRA
How to use pretrained transformers for language tasks and fine-tune them for specific tasks.
How to load models and their inferences and train models with Hugging Face.
Details to know
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Recently updated!
September 2024
Assessments
4 assignments
Taught in English
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There are 2 modules in this course
In this module, you will be introduced to Fine Tuning. You’ll get an overview of generative models and compare Hugging Face and PyTorch frameworks. You’ll also gain insights into model quantization and learn to use pre-trained transformers and then fine-tune them using Hugging Face and PyTorch.
What's included
5 videos4 readings2 assignments4 app items
In this module, you will gain knowledge about parameter efficient fine-tuning (PEFT) and also learn about adapters such as LoRA (Low-Rank Adaptation) and QLoRA (Quantized Low-Rank Adaptation). In hands-on labs you will train a base model and pre-train LLMs with Hugging Face.
What's included
4 videos5 readings2 assignments2 app items4 plugins
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Recommended if you're interested in Machine Learning
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4.4
31 reviews
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- 3 stars
6.45%
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Showing 3 of 31
RK
4
Reviewed on Jan 16, 2025
The labs all too often failed on environment issues - packages, version alignment, etc. This should be seamless in your controlled environment.
SS
5
Reviewed on Nov 16, 2024
The coding part in the labs provided in this course was very helpful and helped me to stabilize my learning.
AE
4
Reviewed on Jan 1, 2025
The course is good but lacks depth on complex subjects.
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Frequently asked questions
It takes about 8 hours to complete this course, so you can have the job-ready skills you need to impress an employer within just one week!
This course is intermediate level, so to get the most out of your learning, you must have basic knowledge of Python, PyTorch, and transformer architecture. You should also be familiar with machine learning and neural network concepts.
This course is part of the Generative AI Engineering with LLMs specialization. When you complete the specialization, you will have the skills and confidence to take on job roles such as AI engineer, NLP engineer, machine learning engineer, deep learning engineer, data scientist, or software developer who want to apply seeking to work with LLMs.