Intermediate course
LLMs Mastery: Complete Guide to Transformers & Generative AI
Generative AI, r1, LLMs, ChatGPT, GPT4, o1, Llama3, Decoders, T5, BERT, LoRA, FSDP, 4bit, Machine Learning, Data Science
Intermediate
Course facts
- Last updated 01/2026
- English English [Auto], Arabic [Auto] , 10 more
- Instructor: The Fuzzy Scientist | LLM Expert
- technical implementation with AI models and applications
What you'll learn
Practical outcomes
- Grasp NLP Fundamentals: Understand the evolution from rule-based systems to advanced LLMs like Llama3, Gemma2, Phi3, and Mistral.
- Master Transformers & LLMs: Learn the architecture and application of Transformers in depth. Including tokenization, embeddings, pre-training & fine-tunning.
- Understand Generative AI Principles: Develop skills in building and fine-tuning generative models for real-world applications using RLHF and Chat-Templates
- Use Transformer Models: Overview LLMs and Encoder-Decoder models like BERT, GPT, T5, Llama and more in many different NLP tasks: Personal assistant, Reviews, QA
- Specialised Techniques: Implement 8-bit and 4-bit training, and use tools like DeepSpeed and FSDP, along with PeFT, LoRA, FlashAttention and more.
Curriculum
12 sections • 52 lectures • 7h 30m total length
1.1 Introduction: Course Overview + What You'll Learn2 lectures • 17min
- Introduction to Part 1 of the Course: Transformers Fundamentals09:51
- Introduction to Part 2 of The Course: LLMs06:44
1.2 Getting Started: How to Make the Best Use of this Course2 lectures • 7min
- Course Structure: How to get the Most out of this Course04:21
- Environment Setup: Prepare and Use the Resource of this Course Right03:03
1.3 Overview of Natural Language Processing: Bring Transformers into Perspective4 lectures • 22min
- Rule-Based Systems Era04:30
- Statistical Era05:34
- Machine Learning Era06:01
- Embeddings Era06:21
- Embeddings Era Quiz 2 questions
1.4 Transformers Introduction: Important Concepts and Use-cases3 lectures • 37min
- Encoders, Decoders and The Attention Mechanism14:03
- Understanding the Transformer Architecture 2 questions
- Pre-training & Fine-tunning12:10
- Tokenisation & Embeddings10:41
- Pre-training and Fine-tuning Transformers 1 question
1.5 Popular Transformers Models: Choose the Best Model for the Job3 lectures • 33min
- BERT13:05
- GPT10:30
- T509:24
- Exploring T5: The Text-to-Text Transfer Transformer 2 questions
1.6 Using Transformers: Building Blocks and Hidden Gems (Practical)5 lectures • 45min
- Building Blocks04:30
- Tokenizers14:24
- Understanding Tokenizers for Transformers 2 questions
- Word Embeddings11:02
- Masked Language Modeling (MLM)06:04
- Masked Language Modeling Quizz 2 questions
- Semantic Search Index09:07
1.7 Mastering Real-World Scenarios with Transformers and LLMs (Practical)3 lectures • 44min
- BERT (Encoder-model) for Extractive Question Answering18:20
- GPT (Decoder-model) for Instruction Following12:50
- Understanding GPT Instruct 2 questions
- T5 (Encoder-Decoder-model) for Writing Product Reviews12:52
- NLP Evolution and Fundamentals 30 questions
2.1 Introduction to Large Language Models6 lectures • 48min
- Decoding Large Language Models: An Introduction08:31
- Introduction to Large Language Models (LLMs) 2 questions
- RLHF: Teaching LLMs to Communicate Effectively08:33
- Understanding Input/Output in Language Models05:43
- Chat Templates: Hands On Overview07:10
- Decision Frameworks for LLM Selection07:20
- Generation: An Interactive Guide10:22
2.2 Preparing for LLM Training (Practical)7 lectures • 56min
- Comprehensive Dive into Sequence Length09:51
- Token Counts: Practical Intuition & Impact07:30
- Precision Matters: Numerical Precision in Training13:32
- Sequences and Tokens 6 questions
- Navigating GPU Selection: A Guide to Hardware Platforms06:00
- Practice Fundamentals: Most Basic Form of Training LLMs04:43
- Practice Fundamentals: Most Basic Form of Training LLMs - Part 208:35
- Practice Fundamentals: Most Basic Form of Training LLMs - Part 305:22
2.3 Advanced LLM Training Techniques (Practical)6 lectures • 59min
- Understanding Practical Limitations05:15
- Boosting Efficiency: PeFT and LoRa in Depth13:37
- Managing Data Memory: Batch Size & Sequence Length08:00
- Advanced Solutions: Gradient Accumulation & Checkpointing13:33
- Fitting Giants: Practical Introduction to LoRA for Large Models10:05
- Expanding LoRA: Adapter Merging and Effective Evaluations08:04
- Advanced Techniques 8 questions
2.4 Exploring Specialised LLM Training Techniques (Practical)5 lectures • 38min
- Level-Up Giants: 8-bit Training for Massive Models06:42
- Task-Focused Training: Aim for Better Learning - Part 109:21
- Task-Focused Training: Aim for Better Learning - Part 205:01
- Edge of Hardware Limits: Scaling Inputs with Flash Attention 208:15
- Edge of Hardware Limits: Reaching 4bit Training with QLoRA08:32
- Specialised Techniques 6 questions
2.5 Scale LLM Training with Advanced Tools (Practical)6 lectures • 45min
- Starting Strong: Introductory Concepts for at Scale Training05:01
- Understanding DeepSpeed: A Theoretical Overview06:30
- Implementing DeepSpeed: A Hands-On Approach08:01
- Scaling Training 3 questions
- FSDP Explained: Theoretical Insights07:31
- Applying FSDP: Real-World Usage and Best Practices08:16
- Wrapping Up: Course Conclusion, Recap, and Future Directions10:04
- LLM Mastery Practice Test 31 questions
Who it is for
- Those who wish to understand the new world of LLMs, how chatGPT, GPT4 and Llama work, and how to build their own powerful language models.
Course description
Overview
Welcome to "LLMs Mastery: Complete Guide to Generative AI & Transformers"! This practical course is designed to equip you with the knowledge and skills to build efficient, production-ready Large Language 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: Start with the basics of LLMs, learning how they decode, process inputs and outputs, and how they are taught to communicate effectively. 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. Advanced Techniques: Sophisticated training strategies like PeFT, LoRa, managing data memory and merging adapters. Specialised Skills: Cutting-edge training techniques, including 8-bit, 4-bit training and Flash-Attention. Scalable Solutions: Master the use of advanced tools like DeepSpeed and FSDP to efficiently scale model training. Course Benefits: • Career Enhancement: Position yourself as a valuable asset in tech teams, capable of tackling significant AI challenges and projects. • Practical Application: Learn by doing—build projects that demonstrate your ability to apply advanced LLM techniques in real-world situations. • Innovative Approach: Stay at the forefront of AI technology by mastering techniques that are shaping the future of machine learning.
What You Will Learn: Natural Language Processing Basics • Journey Through NLP Evolution: From rule-based systems to advanced embeddings. • Foundation in NLP: Set the stage for advanced learning in natural language processing. Introduction to Transformers • Transformer Architecture: Learn about encoders, decoders, and attention mechanisms. • Model Strategies: Understand pre-training, fine-tuning, tokenization, and embeddings. Popular Transformer Models • Explore Key Models: Dive into BERT, GPT, and T5 and their unique capabilities. • Deepen Model Insights: Uncover the potential and versatility of Transformer technology. Using Transformers (Practical) • Hands-On Experience: Apply Transformers in real-world scenarios. • Advanced Techniques: Master tokenization, embeddings, and MLMs. • Project Implementation: Build a Semantic Search Index. NLP Tasks and Applications (Practical) • Real-World Applications: Use BERT for question answering, GPT for personal assistants, and T5 for writing reviews. • Practical NLP Skills: Experience the direct application of NLP tasks. Foundations of Large Language Models • Introduction to LLMs: Understand basic architecture and functionalities. • Communication Techniques: Enhance model responsiveness with RLHF. • Input/Output Processes: Explore how LLMs handle data for AI interactions. Advanced Configuration and Optimization • Chat Template Design: Practical experience in structuring LLM interactions. • Model Selection Frameworks: Strategic decision-making for choosing LLMs. • Generation Techniques: Tailor LLM outputs through interactive learning. Specialized Training Techniques • Advanced Model Training: Focus on sequence length, token counts, and numerical precision. • Efficiency Methods: Learn 8-bit and 4-bit training to adapt models to constraints. • Scaling Tools: Implement DeepSpeed and FSDP for efficient model scaling. Practical Applications of LLMs • Application in Contexts: Apply LLM skills in simulated real-world projects. • Task-Specific Training: Optimize models for specific tasks like memory management and efficiency.
Who This Course Is For: Tech Professionals: Enhance your skills and knowledge in cutting-edge AI technologies. Aspiring AI Practitioners: Get a comprehensive education in LLMs from basic principles to advanced applications. Researchers and Students: Gain a deep understanding of the latest developments and how they can be applied to solve complex problems. Ready to dive into the world of Generative AI and Transformers? Enroll today and start your journey to mastery!
Instructor
The Fuzzy Scientist | LLM Expert
The Fuzzy Scientist | LLM Expert Best Selling Instructor Head of LLM Engineering | Industry Leader | Educator Trusted leader of high-impact projects, I direct teams of ML engineers applying GenAI to solve real-world problems. Involved in enhancing business efficiency and decision-making across the industry, ensuring our projects deliver tangible impacts today. Educator and mentor on Udemy, I guide thousands of students, distilling years of experience into my courses.
