How To Use Large Language Models For Your Business?

Emerging architectures for LLM applications

What you'll learn

- project managers that want to learn about technologies for LLM powererd applications

- developers exploring the emerging stack of LLM applications

- enthusiasts of the large language model technology

- generative AI enthusiasts

- everybody curious about the new LLM and generative AI technology

Requirements

No programming skills needed. The course covers the emerging architectures for llm applications

Description

This course will teach you about Generative AI, Large language models, and their application in business and our workYou’ll start by learning what generative AI and Large language models are. You’ll understand how they work and what areas are most beneficial. You will learn how to use them to enhance your creativity and efficiencyIn the next part, we will dive deeper into methods and technologies used in creating LLM applications like chatbots, AI agents, and AI assistantsLLMs have found promising use cases in various domainsWe are seeing significant changes in domains like programming and gaming, learning, talk-to-your-data applications, search and recommendation systems, sales, marketing, and SEOThe use of AI assistants and chatbots uses the capabilities of LLMs to provide personalized and interactive experiences, leading to increased user engagement and satisfactionPre-trained AI models represent the most important architectural change in software since the internet They make it possible for individual developers to build incredible AI LLM apps in a matter of days, that surpass supervised machine learning projects that took big teams months to buildUnderstanding the strengths and limitations of LLMs and effectively leveraging their capabilities can lead to developing innovative and impactful applications in diverse fieldsWith this course, you will go on a journey through the fascinating world of Generative AI and Large Language Models (LLMs), exploring their transformative impact on the business landscape and workplace efficiencyBegin by unraveling the basics: what Generative AI and LLMs signify, their inner workings, and the domains they excel in. Discover how these advanced technologies can augment your creative prowess and streamline your workflowAs we progress, we'll delve into the intricate methodologies and cutting-edge technologies that underpin LLM applications, such as chatbots, AI agents, and virtual assistants, equipping you with the knowledge to harness their potential to the fullestYou’ll learn about retrieval augmented generation, model fine-tuning, and all the frameworks, all the tools, and processes used in creating LLM-powered applicationsYou’ll learn what is what and how it all fits together. You’ll be able to discuss vector databases, LLMOps, LLM application validation, and all other aspects involved in creating and publishing LLM applicationsThe mission here is to untangle the new paradigm of generative AI and large language models in daily use and in the development world

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 LLMs impact on business

Section 2: Introduction to large language models and generative AI

Lecture 3 What are LLMs and how do they work

Lecture 4 What is Generative AI

Lecture 5 Is generative AI the same as LLM?

Lecture 6 What are the benefits and challenges of using generative AI?

Lecture 7 Benefits and limitations of LLMs

Lecture 8 LLMs and data privacy

Lecture 9 Open source vs propritary LLMs

Lecture 10 Transformer models

Lecture 11 Different types of generative AI models

Lecture 12 AI tools for writing and content creation

Lecture 13 AI tools for design & video production

Lecture 14 AI tools for productivity

Lecture 15 AI tools for eccomerce, sales & marketing

Section 3: Practical applications of LLMs

Lecture 16 Introduction to practical use of LLM applications

Lecture 17 Using LLM applications to automate website creation

Lecture 18 Google SGE

Lecture 19 LLM technology and marketing

Lecture 20 Recruitment and HR

Lecture 21 LLM applications in customer service

Lecture 22 Applications in coding

Lecture 23 LLM applications in tourism

Lecture 24 LLM applications in education

Lecture 25 LLM applications in product development

Lecture 26 Video and audio production

Lecture 27 LLM applications in creative writing

Section 4: Emerging architectures for LLM applications

Lecture 28 Overview of the LLM technologies for LLM applications

Lecture 29 LLM prompt engineering

Lecture 30 LLMs with your custom business knowledge

Lecture 31 Retrieval Augmented Generation - RAG

Lecture 32 Model fine tunning

Lecture 33 AI agents and assistants

Lecture 34 LLM app evaluation

Lecture 35 LLM stack - technologies used in creating LLM applications

Lecture 36 Embedding models and Vector databases

Lecture 37 Vector database list

Lecture 38 How to choose the right LLM for your application

Lecture 39 LLM Playgrounds for testing and playing with LLMs

Lecture 40 Replicate and HuggingFace for open-source models

Lecture 41 Orchestration frameworks like LangChain and llamaIndex

Lecture 42 The difference between LlamaIndex and LangChain

Lecture 43 Logging, Validation, Operational Tools and LLMOps

Lecture 44 LLM Ops Resources

Lecture 45 Opinionated clouds, platforms & hosting list

Lecture 46 Cloud AI solutions

Lecture 47 Security challenges in LLM applications

Section 5: Conclusion

Lecture 48 Conclusion

everybody curious about the new LLM & generative AI technology