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



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