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From Nlp To Llms - A Hands-On Guide For Beginners
![]() 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 |
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