Master Generative AI: Professional level LLM Application Dev

Master Generative AI: Professional level LLM Application Dev | Udemy
English | Size: 13.8 GB
Genre: eLearning

Master Generative AI: Building Professional-Grade LLM Applications for Advanced Solutions

What you’ll learn
Foundations of Generative AI: Understand the core concepts, architectures, and workflows involved in building Generative AI applications.
Working with Large Language Models (LLMs): Explore leading LLMs like GPT-4, Llama, and more, and learn how to integrate them into real-world applications.
Retrieval-Augmented Generation (RAG): Learn RAG concepts, components, and implementation techniques to create efficient AI systems.
LangChain Mastery: Gain hands-on experience with LangChain, including prompt templates, chains, memory management, and advanced RAG capabilities.
Cloud AI Platforms: Work with tools like AWS Bedrock, Google Vertex AI, and other platforms for fine-tuning and deploying AI solutions.
AI Application Development: Build professional-grade applications such as chatbots, sentiment analysis tools, and knowledge systems using advanced frameworks.
Multimodal AI Applications: Learn to implement AI systems that integrate multiple data types, including text, images, and structured data.
LLMOps & Deployment: Understand LLMOps, optimization techniques, and deployment strategies for creating scalable, production-ready AI systems.

Master the art of building professional-grade Generative AI applications with this comprehensive course designed for advanced developers, data scientists, AI enthusiasts, and technology leaders. This program covers everything you need to know about leveraging Large Language Models (LLMs) to create robust, scalable, and production-ready AI-powered solutions. Whether you’re looking to enhance your skills or build innovative applications, this course is your gateway to success in the AI-driven future.

Start with an in-depth exploration of foundational concepts, including the architecture of Generative AI systems, key components, and tools. Learn about advanced topics such as Retrieval-Augmented Generation (RAG), LangChain, LlamaIndex, and the integration of cutting-edge orchestration frameworks. Gain hands-on experience with cloud platforms like AWS Bedrock, Google Vertex AI, and others to fine-tune your applications and deploy them in real-world scenarios.

This course also delves into practical implementations, including chatbots with memory, advanced data retrieval, sentiment analysis tools, and multimodal AI applications. You’ll master essential techniques like managing custom data, creating efficient pipelines, and optimizing performance for scalability. By the end of the course, you’ll have the expertise to design, deploy, and maintain production-level AI systems that exceed professional standards, empowering you to lead in the rapidly evolving field of Generative AI development and innovation.

Who this course is for:
AI Enthusiasts and Developers: Those who want to deepen their understanding of Generative AI and learn how to build professional-grade applications using Large Language Models (LLMs).
Machine Learning Engineers: Professionals looking to enhance their skills in AI application development, particularly in the areas of RAG, LangChain, and LLMOps.
Data Scientists: Individuals aiming to apply advanced AI techniques to solve complex data-related problems, including building intelligent systems and automation.
Cloud Engineers: Developers and engineers interested in using cloud platforms like AWS and Google Cloud to deploy AI applications and fine-tune LLMs.
Software Engineers: Those interested in expanding their expertise to include the integration of advanced AI models into software products.
Tech Entrepreneurs & Innovators: Individuals looking to create AI-powered solutions and products that can disrupt industries or solve real-world problems.
Students & Researchers: Those seeking hands-on experience with cutting-edge AI technologies and frameworks to pursue careers or further studies in AI.
Anyone Interested in Future-Proofing Skills: Individuals eager to stay ahead in the rapidly evolving AI and machine learning fields.

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