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From Nlp To Llms - A Hands-On Guide For Beginners
Published 7/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 52m | Size: 703 MB
Unlocking Language with AI - Your First Step into NLP and LLMs
What you'll learn
Understanding NLP and Introducing Transformers
Understanding Pre-Trained LLMs
Deep Dive into Transformer Architecture
Familiarizing popularly used LLMs (Llama, BERT, GPT)
LLM training vs Fine-tuning for custom tasks
Importance of designing effective prompt design
Ethics, Safety and Future Scope
Capstone Project for creating and deploying your very first Local LLM model
Requirements
Basic knowledge of Python
Overview of AI-Ecosystem
Description
Course OverviewNatural Language Processing (NLP) has evolved rapidly, transforming how machines understand and generate human language. At the forefront of this revolution are Large Language Models (LLMs), which power everything from chatbots to advanced AI systems. This beginner-friendly course takes you on a guided journey from the foundations of NLP to building and deploying your very own LLM-powered application.What's in this course?This course provides a step-by-step introduction to NLP, the rise of transformer-based models, and the practical use of pre-trained LLMs like BERT, GPT, and Llama. Whether you're a student, developer, or enthusiast, you'll gain a practical understanding of how modern language models work and how to leverage them using Python.Through engaging lectures, live demos, and real-world examples, you'll learn:How NLP has evolved and the limitations of early rule-based methodsThe inner workings of transformer architectureKey differences between popular LLMs like BERT and GPTHow to interact with LLMs using Hugging FacePrompt engineering techniques to guide model outputsHow to integrate LLMs into real applications and optimize them for deploymentEthical challenges and the future scope of language modelsHow to build and deploy your first LLM-powered chatbot using FlaskSpecial Note: This course emphasizes hands-on implementation using Python and vs code. Every concept is paired with a hands-on demonstration, ensuring you not only understand the theory but also gain practical skills in using LLMs effectively.Course Structure:LecturesDemosReal World Examples/ApplicationsCapstone ProjectCourse Contents:Course IntroductionGetting started with NLP and limitations of traditional approaches"Attention is All You Need"-Rise of TransformersDeep Dive into Transformer ArchitectureFamiliarizing popularly used LLMs (Llama, BERT, GPT)LLM training vs Fine-tuning for custom tasksImportance of designing effective prompt designZero-shot vs Few-shot learningOptimizing deployment cost and latencyBias, Toxicity and Fairness challengesMitigating risks to enhance safetyFuture scope for LLMsCapstone project - Creating and Deploying your very first Local LLM modelBy the end of this course, you'll be confident in understanding and working with Large Language Models. You'll be able to build, fine-tune, and integrate LLMs into real-world applications and responsibly navigate their ethical implications.
Who this course is for
Beginners in NLP & LLMs
AI/ML Engineers
Data Scientists & Developers working with text data and model integration
Tech Leads & Product Managers exploring LLM applications in products
AI/GenAI Enthusiasts curious to build and deploy their first LLM-based project
