What you'll learn:
- Design Scalable GenAI Applications: Learn to architect and build scalable GenAI applications using the LGPL architecture, focusing on Layer, Gate, Pipes
- Implement Resiliency and Error Handling: Understand how to incorporate error handling, monitoring, logging, and disaster recovery to create resilient GenAI Apps
- Ensure Security and Cost Efficiency: Develop secure and cost-effective GenAI solutions by leveraging AWS security services, containerization
- Automate and Optimize with MLOps & CI/CD: Learn to implement MLOps, CI/CD, and Explainable AI (XAI) for streamlined deployment and future-proofing GenAI apps
Master the essential techniques and best practices for designing and architecting scalable, secure, and cost-effective Generative AI (GenAI) applications.
In this course, you’ll explore the principles of the LGPL architecture (Layers, Gates, Pipes, and Loops) and how they apply to building GenAI systems using modern cloud services like AWS.
We’ll cover critical topics such as load balancing, containerization, error handling, monitoring, logging, and disaster recovery. This course is ideal for those looking to understand GenAI architecture, ensuring applications are resilient, secure, and efficient.
What You'll Learn:
Architect scalable and secure GenAI applications using the LGPL model.
Understand core concepts such as containerization, load balancing, and disaster recovery.
Learn best practices for monitoring, logging, and error handling in GenAI systems.
Explore MLOps, CI/CD, and security strategies for future-proofing AI applications.
This course focuses on the architecture and principles behind building robust GenAI systems, providing the knowledge needed to design effective AI solutions.
Enroll now to transform your GenAI Application Architecture skills to the next level. Master GenAI Application Architecture - the core best practices and techniques for building secure, efficient, scalable GenAI Applications.
Ready to take your skills to the next level? Join me, and let's get started.
See you inside the course!
