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Essentials of Large Language Models: A Beginner’s Journey

In this LLM course, learn the fundamentals, fine-tuning, and evaluation, and explore its architecture and evolution. Discover GPT-2, compare models, and uncover use cases.

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Overview

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In this course, you will acquire a working knowledge of the capabilities and types of LLMs, along with their importance and limitations in various applications. You will gain valuable hands-on experience by fine-tuning LLMs to specific datasets and evaluating their performance. You will start with an introduction to large language models, looking at components, capabilities, and their types. Next, you will be introduced to GPT-2 as an example of a large language model. Then, you will learn how to fine-tune a selected LLM to a specific dataset, starting from model selection, data preparation, model training, and performance evaluation. You will also compare the performance of two different LLMs. By the end of this course, you will have gained practical experience in fine-tuning LLMs to specific datasets, building a comprehensive skill set for effectively leveraging these generative AI models in diverse language-related applications.

In this course, you will acquire a working knowledge of the capabilities and types of LLMs, along with their importance and limi...Show More

WHAT YOU'LL LEARN

An understanding of language models, large language models, and their key differences

Familiarity with the components of LLMs and their basic architecture

Working knowledge of the types of LLMs, along with their importance and limitations

An understanding of GPT-2 as a large language model

Hands-on experience fine-tuning LLMs to specific datasets and evaluating their performance

An understanding of language models, large language models, and their key differences

TAKEAWAY SKILLS

Generative AI

Large Language Models (LLMs)

Content

15 Lessons3 Quizzes

Course Overview

1 Lessons

Get familiar with large language models, their applications, and ethical considerations in AI.

Introduction to the Course

Getting Started with LLMs

7 Lessons

Learn about advanced LLM fundamentals, components, types, capabilities, examples, and limitations.

Large Language Models

The Transformer Architecture

Evolution of LLMs

Capabilities of LLMs

Example LLM: GPT-2

Exploring Use Cases of LLMs

Importance and Limitations

Fine-Tuning LLMs

6 Lessons

Examine fine-tuning LLMs, model selection, data preparation, training, evaluation, and performance comparison.

Wrap Up

1 Lessons

Learn about applying language models creatively and responsibly to impact AI.

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

Trusted by 2.8 million developers working at companies

"Very good insight about overall AI evaluation and sample model training."

Ramesh Perla

Senior Software Engineer @ Microsoft

"I thought this course was a great general overview of LLMs that introduced the main concepts and context of LLMs within the world of AI, how they work at a high level, and how their performance is measured."

Jorge Astorga

AI Technical Program Manager @ Cruise

"These are high-quality courses. Trust me. I own around 10 and the price is worth it for the content quality. EducativeInc came at the right time in my career. I'm understanding topics better than with any book or online video tutorial I've done. Truly made for developers. Thanks"

Anthony Walker

@_webarchitect_

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Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

Explain with AI

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AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

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Frequently Asked Questions

What is the basic of LLM?

The basics of LLMs include understanding neural networks, transformers, large datasets, and the processes of pre-training and fine-tuning to enable the model to generate human-like text.

Is GPT an LLM?

Yes, GPT (Generative Pre-trained Transformer) is a type of LLM developed by OpenAI, known for its ability to generate coherent and contextually relevant text based on the input it receives.

What is the difference between LLM and AI?

AI (Artificial Intelligence) is a broad field encompassing the creation of intelligent systems, while LLM (Large Language Model) is a specific type of AI focused on understanding and generating human language; LLMs are a subset or tool within the broader field of AI.

What does LLM include?

LLMs include neural networks with millions or billions of parameters, trained on vast datasets of text, and include components for tokenization, embedding, attention mechanisms, and output generation to process and generate human-like language.

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