Overview

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Advance your skills in designing, fine-tuning, and deploying sophisticated Generative AI applications, from agent architectures to production-ready systems. Gain the expertise to architect, optimize, and scale AI-powered solutions for real-world impact. This course focuses on advanced topics in Generative AI application design, including specialized architectures, reinforcement learning, and agentic AI. Learners will explore fine-tuning techniques, benchmarking, and user-centric deployment strategies, culminating in the end-to-end process of building and launching a production-grade AI application. By mastering these advanced practices, learners will be prepared to deliver scalable, secure, and high-performing AI solutions. Through in-depth readings, expert video instruction, and targeted assessments, this course provides a comprehensive pathway from advanced architecture design to production deployment. Learners will gain actionable insights and frameworks to architect, optimize, and operationalize Generative AI applications in diverse domains. This course is part three of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Generative AI for Software Developers, by Saurabh Shrivastava, Kamal Arora, Ashutosh Dubey, Dhiraj Thakur and Sanjeet Sahay. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

Generative AI Application Architecture and Design
- This module explores the unique architecture and design principles of generative AI applications, covering topics such as data flow, context-aware frameworks, and integration with real-world systems. Learners will gain insights into how to build scalable, efficient AI solutions using techniques like RAG, LangChain, and map-reduce architectures. The module emphasizes practical implementation and adaptation of generative AI in diverse scenarios.
Reinforcement Learning and AI Agent Architecture Design
- This module covers the fundamentals of reinforcement learning and the design of AI agents, focusing on dynamic decision-making, reward models, and real-world applications like travel assistants and function calling. Learners will gain an understanding of how AI systems learn from feedback and adapt to complex tasks.
Well-Architecting and Fine-tuning GenAI Application
- This module covers strategies for building scalable, secure, and efficient Generative AI (GenAI) applications. It explores techniques like fine-tuning, evaluation with ROUGE and BLEU metrics, and system design considerations such as context awareness and user-centric approaches. Learners will gain practical skills in optimizing and deploying AI systems effectively.
Building a GenAI App from Prototype to Production
- This module covers the process of transforming a GenAI prototype into a production-ready application. Learners will explore system design, API integration, deployment strategies, and security practices to ensure scalable and secure AI-driven solutions.