LLMs Workshop- Practical Exercises of Large Language Models

LLMs Workshop: Practical Exercises of Large Language Models, available at $44.99, has an average rating of 4.55, with 26 lectures, 1 quizzes, based on 52 reviews, and has 1381 subscribers.

You will learn about Deep Learning Transformers Langchain Large Language Models This course is ideal for individuals who are Deep learning Engineers or Deep Learning enthusiasts or Machine Learning Engineers or Artificial intelligence Engineers It is particularly useful for Deep learning Engineers or Deep Learning enthusiasts or Machine Learning Engineers or Artificial intelligence Engineers.

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Summary

Title: LLMs Workshop: Practical Exercises of Large Language Models

Price: $44.99

Average Rating: 4.55

Number of Lectures: 26

Number of Quizzes: 1

Number of Published Lectures: 26

Number of Published Quizzes: 1

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

Deep Learning

Transformers

Langchain

Large Language Models

Who Should Attend

Deep learning Engineers

Deep Learning enthusiasts

Machine Learning Engineers

Artificial intelligence Engineers

Target Audiences

Deep learning Engineers

Deep Learning enthusiasts

Machine Learning Engineers

Artificial intelligence Engineers

Dive into the revolutionary world of Large Language Models (LLMs) with our comprehensive 4-hour workshop, designed to bridge the gap between theoretical knowledge and practical skills. Whether you’re a budding data scientist, an AI enthusiast, or a seasoned professional looking to expand your toolkit, this course is tailored to empower you with hands-on experience in leveraging LLMs for a variety of real-world applications.

What You’ll Learn:

Fundamentals and Advanced Techniques: Start with the basics of Large Language Models, including their architecture and capabilities, before progressing to advanced optimization methods such as Quantization and LoRA.

Practical Exercises: Engage in structured exercises using Kaggle datasets in Colab, fine-tuning models for tasks like question answering and text summarization with QLoRA, and exploring cutting-edge concepts such as Retrieval Augmented Generation (RAG).

Real-World Applications: Tackle engaging projects like building a semantic search engine to find movies and developing a chat interface with scholarly articles, applying your knowledge in tangible, impactful ways.

Model Publication: As a bonus, learn how to share your fine-tuned models with the world through Huggingface, enhancing your visibility in the AI community.

Intended Learners:

This course is perfect for individuals looking to deepen their understanding of LLMs and apply these models in innovative ways. Ideal for AI professionals, data scientists, and researchers eager to expand their skills and apply LLMs to solve complex problems.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: How to use any dataset on Kaggle in Colab

Lecture 3: LLMs Training Optimization Methods – Quantization & LoRA

Lecture 4: What is RAG ?

Lecture 5: Evaluation Methods for LLMs

Chapter 2: Full Fine-tuning for Question Answering

Lecture 1: Introduction to the problem & the dataset

Lecture 2: Data preparation

Lecture 3: Model and tokenizer

Lecture 4: Training

Lecture 5: Evaluation and Testing

Chapter 3: Fine-tuning for News-Text Summarization (QLoRA)

Lecture 1: Introduction to the problem & the dataset

Lecture 2: Data preparation

Lecture 3: Tokenizer

Lecture 4: Model Preparation

Lecture 5: Training

Lecture 6: Evaluation

Lecture 7: Extra: Publish your model on Huggingface

Chapter 4: Find your movie – Semantic Search

Lecture 1: Introduction to the problem & dataset

Lecture 2: Data Preparation

Lecture 3: Vector Database creation

Lecture 4: Testing

Chapter 5: Chat with your paper – Retrieval Augmented Generation (RAG)

Lecture 1: Introduction to the problem & dataset

Lecture 2: Data Preparation & Preprocessing

Lecture 3: Vector Database creation

Lecture 4: LLM Prompt Integration & Model

Lecture 5: Testing

Instructors

Omar Elgendy
AI Engineer

Rating Distribution

1 stars: 0 votes

2 stars: 1 votes

3 stars: 6 votes

4 stars: 13 votes

5 stars: 32 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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