Practical NLP With Transformers

This course is conducted live and features industry experts to deliver top-notch information, enhancing your knowledge and understanding.

Welcome to “Practical NLP With Transformers,” a dynamic and hands-on course designed for students, developers, and data scientists who wish to delve into the world of Natural Language Processing (NLP) using transformer models. This course combines theoretical knowledge with practical skills, guiding you through the latest advancements in NLP and the use of transformer models like LLAMA, Falcon, GPT, and T5.

Course Objectives:
1. Understanding the Basics of NLP: Grasp the fundamental concepts of NLP, including tokenization, part-of-speech tagging, named entity recognition, and sentiment analysis.
2. Exploring Transformer Architecture: Dive deep into the workings of transformer models, understanding their unique architecture and how they differ from traditional RNNs and CNNs.
3. Hands-On Training with Pre-Trained Models: Learn to implement pre-trained models like LLAMA/Falcon in real-world scenarios, and understand their strengths and limitations.
4. Custom Model Training and Fine-Tuning: Gain skills in training and fine-tuning transformer models on custom datasets for specialized tasks.
5. Application in Various Domains: Explore the application of transformers in various domains like chatbots, text generation, language translation, and more.

Course Modules:

1. Introduction to NLP and Transformers
   1. Overview of NLP
   2. Evolution of Language Models
   3. Introduction to Transformer Architecture
2. Working with Pre-Trained Transformer Models
   1. Implementing LLAMA/Falcon
   2. Exploring GPT for text generation
   3. Utilizing T5 for translation tasks
3. Advanced Techniques in Transformers
   1. Transformer model fine-tuning techniques
   2. Custom dataset preparation and model training
   3. Performance optimization and scalability
4. Real-World Applications and Case Studies
   1. Case studies in different industry domains
   2. Building end-to-end NLP applications
   3. Integration of NLP models in software applications

Target Audience:This course is ideal for students with a basic understanding of machine learning and Python programming, as well as data scientists and developers looking to specialize in NLP.

Prerequisites: Basic knowledge of Python programming, machine learning concepts, and familiarity with deep learning frameworks.

Join us on this exciting journey to master the art of NLP with transformers, and empower your career in the world of AI and machine learning!