LLMs Mastery Complete Guide to Transformers Generative AI

Generative AI, LLMs, ChatGPT, GPT4, Production-Level, Encoder-Decoders, T5, GPT2, BERT, Machine Learning, Data Science
LLMs Mastery Complete Guide to Transformers Generative AI
File Size :
1023.68 MB
Total length :
2h 6m



The Fuzzy Scientist


Last update




LLMs Mastery Complete Guide to Transformers Generative AI

What you’ll learn

Grasp NLP Fundamentals: Understand the evolution and key concepts of Natural Language Processing, from rule-based systems to the deep learning era.
Master Transformers: Learn the architecture and application of Transformers in depth. Including tokenization, embeddings, pre-training & fine-tunning.
Understand the principles behind Generative AI: Get familiar with building and tweaking generative models for any real-world use case.
Utilize Transformer Models: Overview LLMS and Encoder-Decoder models like BERT, GPT, and T5 in various NLP tasks.
Develop practical, useful and production ready NLP tasks: Build personal assistants, model for writing product reviews and answering questions..

LLMs Mastery Complete Guide to Transformers Generative AI


Basic understanding of Python programming, some basic familiarity with machine learning concepts, and a strong eagerness to delve into LLMs and text analysis..


Welcome to “LLMs Mastery: Complete Guide to Generative AI & Transformers”!This comprehensive guide is designed to equip you with the knowledge and skills to build efficient, production-ready AI models using cutting-edge technologies.Key Topics Covered:Generative AI: Understand the principles and applications of Generative AI in creating new data instances.ChatGPT & GPT4: Dive into the workings of advanced AI models like ChatGPT and GPT4.LLMs: Learn about Language Models (LLMs) and their role in understanding and generating human-like text.Encoder-Decoders: Master the concept of encoder-decoder models in the context of Transformers.T5, GPT2, BERT: Get hands-on experience with popular Transformer models such as T5, GPT2, and BERT.Machine Learning & Data: Understand the role of machine learning and data in training robust AI models.What You Will Learn:Natural Language Processing Basics️ Journey through the evolution of NLP, from the Rule-Based Systems Era to the Embeddings Era.️ Lay a solid foundation in NLP for more advanced topics.Introduction to TransformersLearn about the architecture of Transformer models, including attention mechanisms, encoders, and decoders.️ Understand pre-training and fine-tuning strategies.Explore tokenization and embeddings, critical components of Transformer models.Popular Transformer ModelsDive into popular Transformer models: BERT (encoder-only), GPT (decoder-only), and T5 (encoder-decoder).Gain deeper insights into the capabilities and potential of Transformer technology.Using Transformers (Practical)Get hands-on experience with Transformer models in real-world applications.Master tokenization, embeddings, and masked language models (MLMs).Build a Semantic Search Index project.NLP Tasks and Applications (Practical)Learn how to use BERT for extractive question answering, GPT for building a personal assistant, and T5 for writing product reviews.Experience the practical applications of NLP tasks.Who This Course Is For:‍ Perfect for anyone interested in AI, machine learning, and data science.Ideal for both seasoned professionals and curious beginners.Ready to dive into the world of Generative AI and TransformersEnroll today and start your journey to mastery!


Section 1: Introduction

Lecture 1 Introduction

Section 2: Getting Started: How to Make the Best Use of this Course

Lecture 2 Setup and How-To

Section 3: Overview of Natural Language Processing: Bring Transformers into Perspective

Lecture 3 Rule-Based Systems Era

Lecture 4 Statistical Era

Lecture 5 Machine Learning Era

Lecture 6 Embeddings Era

Section 4: Transformers Introduction: Important Concepts and Use-cases

Lecture 7 Encoders, Decoders and The Attention Mechanism

Lecture 8 Pre-training & Fine-tunning

Lecture 9 Tokenisation & Embeddings

Section 5: Popular Transformers Models: Choose the Best Model for the Job

Lecture 10 BERT

Lecture 11 GPT

Lecture 12 T5

Section 6: Using Transformers: Building Blocks and Hidden Gems (Practical)

Lecture 13 Building Blocks

Lecture 14 Tokenizers

Lecture 15 Word Embeddings

Lecture 16 Masked Language Modeling (MLM)

Lecture 17 Semantic Search Index

Section 7: Mastering Real-World Scenarios with Transformers and LLMs (Practical)

Lecture 18 BERT (Encoder-model) for Extractive Question Answering

Lecture 19 GPT (Decoder-model) for Instruction Following

Lecture 20 T5 (Encoder-Decoder-model) for Writing Product Reviews

Those who wish to understand the new world of LLMs, how chatGPT and GPT4 work, and how to build their own powerful language models.

Course Information:

Udemy | English | 2h 6m | 1023.68 MB
Created by: The Fuzzy Scientist

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