"Mastering Language Models: Unleashing The Power Of Llms"

A Comprehensive Guide to Advanced NLP and Large Language Models (LLMs)

What you'll learn

Understand the Fundamentals of Language Models and Natural Language Processing (NLP)

Master the Application of Pre-trained Language Models

Analyze and Address Challenges in Language Model Implementation

Build and Deploy Custom Language Model Projects

Requirements

Basic Programming Skills: Familiarity with programming concepts and Python.

Fundamental Knowledge of NLP: Understanding of tokenization, part-of-speech tagging, and text preprocessing.

Machine Learning Basics: General knowledge of supervised/unsupervised learning, training/testing data, and model evaluation.

Neural Networks and Deep Learning: Familiarity with neural networks, activation functions, and backpropagation.

Mathematics Fundamentals: Basic understanding of linear algebra and calculus (optional).

Python Environment: Access to a text editor, Python, and relevant libraries.

Description

Are you ready to unlock the full potential of Large Language Models (LLMs) and revolutionize your understanding of Natural Language Processing (NLP)? Welcome to "Mastering Language Models: Unleashing the Power of LLMs," where you'll embark on a transformative journey through the cutting-edge world of advanced NLP and the remarkable capabilities of LLMs.In this comprehensive course, you'll delve into the fundamental principles of NLP and explore how LLMs have reshaped the landscape of AI applications. You'll gain a solid grasp of essential NLP concepts, including tokenization, word embeddings, attention mechanisms, and the transformative role of Transformer architecture in LLMs.Our hands-on approach will lead you through harnessing the potential of pre-trained models like BERT, GPT-3, and others, as we guide you in fine-tuning them for specific NLP tasks. From text generation and classification to translation and question-answering systems, you'll discover the vast range of applications for these powerful language models.As we progress, we'll address crucial challenges related to bias and fairness in LLMs, handling out-of-domain data, and ensuring ethical AI development. Through practical examples and exercises, you'll develop the skills to create robust language model projects and overcome real-world obstacles.Led by our experienced instructor, Abhishek Gautam, a seasoned AI researcher, and educator, this course fosters an engaging learning environment. Abhishek's passion for AI and his commitment to empowering learners will guide you through the complexities of NLP and LLMs, making even the most intricate concepts accessible to learners of all backgrounds.Whether you're a data scientist, developer, researcher, or AI enthusiast, this course is designed to propel you to the forefront of AI-driven innovations. Join us on this transformative journey, and together, let's master Large Language Models and unleash the power of NLP to shape a smarter and more connected world.Enroll today and take the first step towards becoming an NLP expert and a master of Large Language Models!

Overview

Section 1: Introduction to Language Models and NLP

Lecture 1 Introduction and Welcome

Lecture 2 Introduction to Language Models

Lecture 3 Exploring Large Language Models (LLMs)

Lecture 4 The Mechanics of LLMs

Lecture 5 Applications of LLMs

Lecture 6 Benefits and Challenges of LLMs

Lecture 7 Conclusion of Section 1 and What's Next

Section 2: Understanding Large Language Models (LLMs)

Lecture 8 Introduction and Overview

Lecture 9 Fundamental Techniques Used in NLP

Lecture 10 Tokenization

Lecture 11 Word Embeddings

Lecture 12 Attention Mechanishm

Lecture 13 Self Attention

Lecture 14 Transformer in Large Language Models

Lecture 15 Conclusion and Preview of Next Section

Section 3: Preparing for LLM Experiments: Setting up the Stage!

Lecture 16 Introduction

Lecture 17 Unraveling the Journey So Far!

Lecture 18 Exploring the Versatility of Large Language Models (LLMs)

Lecture 19 Conclusion

Section 4: Fine-Tuning Large Language Models

Lecture 20 Introduction

Lecture 21 Process of Finetuning LLMs Explained

Lecture 22 [Practical] Finetuning GPT2 model for Text Generation - Part A

Lecture 23 [Practical] Finetuning GPT2 model for Text Generation - Part B

Lecture 24 Conclusion

Data Scientists and NLP Practitioners: Enhance expertise in LLMs like BERT and GPT-3 for specific NLP tasks.,AI and Machine Learning Enthusiasts: Explore cutting-edge language model advancements and develop AI-driven applications.,Software Engineers and Developers: Integrate language models into applications and build custom models.,Students and Researchers in NLP: Comprehensive coverage of language models for study and research.,Entrepreneurs and Innovators: Discover AI-powered solutions involving NLP for products or services.,Data Analysts and Linguists: Leverage language models for text analysis and NLP tasks.,Professionals Seeking Career Advancement: Stay competitive in industries utilizing LLMs.