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.
Enroll now: LLMs Workshop: Practical Exercises of Large Language Models
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:
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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.
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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).
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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.
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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
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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
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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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