Intro to Large Language Models (LLMs)

Intro to Large Language Models (LLMs), available at $44.99, has an average rating of 4.51, with 44 lectures, based on 207 reviews, and has 1237 subscribers.

You will learn about Transformer architecture fundamentals Concepts of attention and self-attention Utilizing OpenAI's API Text embeddings in LLMs Introduction to LangChain Exploring Hugging Face's tools This course is ideal for individuals who are Developers looking to enhance their skills in AI and machine learning or Data Scientists interested in expanding their expertise in natural language processing or Tech Enthusiasts and students eager to explore the latest in AI technology or Product Managers and entrepreneurs aiming to incorporate AI into their products It is particularly useful for Developers looking to enhance their skills in AI and machine learning or Data Scientists interested in expanding their expertise in natural language processing or Tech Enthusiasts and students eager to explore the latest in AI technology or Product Managers and entrepreneurs aiming to incorporate AI into their products.

Enroll now: Intro to Large Language Models (LLMs)

Summary

Title: Intro to Large Language Models (LLMs)

Price: $44.99

Average Rating: 4.51

Number of Lectures: 44

Number of Published Lectures: 44

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Transformer architecture fundamentals
Concepts of attention and self-attention
Utilizing OpenAI's API
Text embeddings in LLMs
Introduction to LangChain
Exploring Hugging Face's tools

Who Should Attend

Developers looking to enhance their skills in AI and machine learning
Data Scientists interested in expanding their expertise in natural language processing
Tech Enthusiasts and students eager to explore the latest in AI technology
Product Managers and entrepreneurs aiming to incorporate AI into their products

Target Audiences

Developers looking to enhance their skills in AI and machine learning
Data Scientists interested in expanding their expertise in natural language processing
Tech Enthusiasts and students eager to explore the latest in AI technology
Product Managers and entrepreneurs aiming to incorporate AI into their products

Do you want to learn about Large Language Models and AI?

Are you ready to dive into the world of Artificial Intelligence and develop skills that are in high demand across various industries?

Our Introduction to Large Language Models course is your gateway to understanding and leveraging the capabilities of AI to revolutionize how we interact with technology.

Why Learn About Large Language Models?

In recent years, Large Language Models (LLMs) like GPT, BERT, and XLNet have transformed tech landscapes, powering everything from conversational AI to advanced text analysis. The ability of these models to generate text, understand language, and even write code has made them a pivotal area in AI research and application.

Course Curriculum at a Glance:

Introduction to LLMs: Explore the capabilities and functions of state-of-the-art language models.
The Transformer Architecture: Understand the groundbreaking architecture that powers most modern LLMs.
Getting Started with GPT Models: Dive into generating text and building applications using GPT.
Hugging Face Transformers: Learn to use one of the most popular platforms for deploying LLMs.
Question and Answer Models with BERT: Create sophisticated QA systems using BERT.
Text Classification with XLNet: Tackle complex text classification tasks with advanced techniques.

What Will You Gain?

This course is designed not just to teach you the theory but to equip you with practical skills through:

Engaging Video Lessons: Delivered by industry experts, these lessons break down complex concepts into digestible segments
Hands-On Coding Exercises: Apply what you learn in real-world scenarios, from building chatbots to text analysis
Comprehensive Coverage: From the basics of what LLMs are to the intricacies of transformer architecture and fine-tuning models for specific tasks
Project-Based Learning: Implement LLMs in your own projects, fine-tune models for unique data sets, and solve practical NLP tasks

Take the Next Step in Your AI Journey

Enroll now and start transforming your understanding of AI and your career trajectory with our expert-led Large Language Models course. Whether you’re looking to innovate in your current role or pivot to a completely new field, mastering LLMs will give you a competitive edge in the fast-evolving tech landscape.

Join us today and be a part of the AI revolution!

Course Curriculum

Chapter 1: Introduction to Large Language Models

Lecture 1: Introduction

Lecture 2: Course materials and notebooks

Lecture 3: What are LLMs?

Lecture 4: How large is an LLM?

Lecture 5: General purpose models

Lecture 6: Pre-training and fine tuning

Lecture 7: What can LLMs be used for?

Chapter 2: The Transformer Architecture

Lecture 1: Deep learning recap

Lecture 2: The problem with RNNs

Lecture 3: The solution: attention is all you need

Lecture 4: The transformer architecture

Lecture 5: Input embeddings

Lecture 6: Multi-headed attention

Lecture 7: Feed-forward layer

Lecture 8: Masked multihead attention

Lecture 9: Predicting the final outputs

Chapter 3: Getting started with GPT models

Lecture 1: What does GPT mean?

Lecture 2: The development of ChatGPT

Lecture 3: OpenAI API

Lecture 4: Generating text

Lecture 5: Customizing GPT Output

Lecture 6: Keyword text summarization

Lecture 7: Coding a simple chatbot

Lecture 8: Introduction to Langchain in Python

Lecture 9: Langchain

Lecture 10: Adding custom data to our chatbot

Chapter 4: Hugging Face Transformers

Lecture 1: Hugging Face package

Lecture 2: The transformer pipeline

Lecture 3: Pre-trained tokenizers

Lecture 4: Special tokens

Lecture 5: Hugging Face and PyTorch, TensorFlow

Lecture 6: Saving and loading models

Chapter 5: Question and answer models with BERT

Lecture 1: GPT vs BERT

Lecture 2: BERT architecture

Lecture 3: Loading the model and tokenizer

Lecture 4: BERT embeddings

Lecture 5: Calculating the response

Lecture 6: Creating a QA bot

Lecture 7: BERT, RoBERTa, DistilBERT

Chapter 6: Text classification with XLNet

Lecture 1: GPT vs BERT vs XLNET

Lecture 2: Preprocessing our data

Lecture 3: XLNet Embeddings

Lecture 4: Fine tuning XLNet

Lecture 5: Evaluating our model

Instructors

365 Careers
Creating opportunities for Data Science and Finance students
Lauren Newbould
Data Scientist

Rating Distribution

1 stars: 3 votes
2 stars: 2 votes
3 stars: 17 votes
4 stars: 83 votes
5 stars: 102 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?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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