Beyond the Sequence: The Transformer and LLM Revolution Training Course

Introduction

Transformer models have revolutionized the field of natural language processing (NLP) by moving beyond the limitations of sequential processing. They are the backbone of modern Large Language Models (LLMs) like GPT and BERT, enabling a new generation of applications from advanced chatbots to sophisticated code generation and creative content creation. This course is designed to provide you with a deep understanding of the inner workings of these models and how to build, fine-tune, and deploy them.

This five-day, hands-on program will guide you from the foundational concepts of self-attention to the practical application of fine-tuning large-scale models for specific tasks. You'll learn to work with pre-trained models and master the techniques that power today's most intelligent AI systems. By the end, you will have the skills and knowledge to create powerful, context-aware applications that leverage the full potential of transformers and LLMs.

Duration 5 days

Target Audience This course is for data scientists, machine learning engineers, and NLP specialists who have a solid background in neural networks and are looking to specialize in modern NLP techniques. Experience with Python and a deep learning framework like TensorFlow or PyTorch is required.

Objectives

  • To understand the fundamental principles and architecture of the Transformer model.
  • To master the concept of self-attention and its role in modern LLMs.
  • To learn how to apply pre-trained models like BERT and T5 to solve various NLP tasks.
  • To gain hands-on experience with fine-tuning LLMs for specific applications.
  • To explore advanced techniques like transfer learning and few-shot learning.
  • To understand the challenges and ethical considerations of working with LLMs.
  • To build and train an end-to-end model for a real-world NLP project.
  • To gain an introduction to prompt engineering and its importance.
  • To develop a systematic approach to evaluating and comparing LLM performance.
  • To explore the basics of model deployment for real-world scenarios.

Course Modules

Module 1: The Attention Revolution

  • An overview of the limitations of RNNs and LSTMs.
  • The core idea behind attention mechanisms.
  • The "Attention Is All You Need" paper and the birth of the Transformer.
  • A conceptual walkthrough of the self-attention mechanism.
  • A hands-on exercise to build a simple attention-based model.

Module 2: The Transformer Architecture

  • The components of the Transformer encoder and decoder.
  • The role of positional encoding.
  • Understanding multi-head attention.
  • The feed-forward network and residual connections.
  • A visual breakdown of the complete Transformer block.

Module 3: Pre-Trained Transformers

  • The concept of pre-training and fine-tuning.
  • A deep dive into the BERT (Bidirectional Encoder Representations from Transformers) model.
  • The architecture and use cases for GPT (Generative Pre-trained Transformer).
  • Understanding the differences between encoder-only, decoder-only, and encoder-decoder models.
  • A practical guide to using the Hugging Face Transformers library.

Module 4: Fine-Tuning a Transformer Model

  • The process of fine-tuning a pre-trained model for a new task.
  • Strategies for freezing layers and training the final layers.
  • A hands-on project to fine-tune a model for sentiment analysis.
  • The importance of a well-structured dataset for fine-tuning.
  • A discussion on the compute requirements for fine-tuning.

Module 5: Transfer Learning and Few-Shot Learning

  • The power of transfer learning in the context of LLMs.
  • The concept of few-shot learning, in which models learn from a small number of examples.
  • The role of in-context learning.
  • A hands-on exercise to apply few-shot learning to a simple task.
  • A discussion on the trade-offs between fine-tuning and few-shot learning.

Module 6: Prompt Engineering

  • The art and science of writing effective prompts for LLMs.
  • Techniques for crafting clear and specific instructions.
  • The importance of providing context and constraints.
  • A hands-on exercise with various prompting strategies.
  • A discussion on the future of prompt engineering.

Module 7: Evaluation of LLMs

  • Metrics for evaluating the performance of LLMs.
  • The importance of human-in-the-loop evaluation.
  • The use of RAG (Retrieval-Augmented Generation) for evaluation.
  • The concept of the perplexity score.
  • A practical guide to setting up an evaluation pipeline.

Module 8: The Ethics of LLMs

  • The societal impact of large language models.
  • Addressing bias in training data.
  • The challenges of misinformation and malicious use.
  • Strategies for mitigating ethical risks.
  • A discussion on the responsibility of developers and researchers.

Module 9: Advanced Techniques

  • The use of LoRA (Low-Rank Adaptation) for efficient fine-tuning.
  • The concept of model distillation to create smaller models.
  • A discussion on the latest research in the field.
  • A practical guide to exploring new architectures.
  • A demonstration of how to contribute to the open-source community.

Module 10: Model Deployment

  • The challenges of deploying a large model in production.
  • Strategies for optimizing a model for inference.
  • The use of APIs to access pre-trained models.
  • A conceptual guide to setting up a web service for your model.
  • A discussion on monitoring and maintenance.

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport Pick Up is provided by the institute. Accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

Beyond The Sequence: The Transformer And Llm Revolution Training Course in Namibia
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