Deploying and Evaluating GenAI Apps Learning Badge Path

Welcome. Have you joined the ever growing club of AI developers and built your own GenAI application? Awesome work. But now what? You probably want to make sure it's running optimally and are eager to put it in front of real users.

After completing this learning badge, you'll be able to do just that. If you haven't built your own GenAI app yet, check out our Building a GenAI App with MongoDB Learning Badge Path to learn how and earn another badge.

By going through this learning path, you'll take your GenAI app from creation to full deployment, optimizing it along the way. Keep in mind that this process is cyclical, so it's perfectly normal to revisit these steps as your application changes and evolves.

We will begin with chunking strategies to enhance the performance of GenAI applications by splitting data into smaller pieces for better accuracy. We'll cover three methods: recursive splitting, document specific splitting, and semantic splitting, with guidance on tailoring the approach based on your application's needs. 

We'll also explore how to evaluate the performance of your GenAI app. This is a broad and ever growing topic, but we'll break it down by highlighting key concepts and areas that help you gauge how well your app is functioning and identify opportunities for improvement.

You'll also learn about useful techniques and tools to effectively assess your app's results and enhance its performance.

No GenAI application would be complete without being deployed on a database. Whether you are ready for production or still in the prototyping phase, MongoDB provides environments that will suit the needs of your app. We will outline options for prototyping, like local clusters or shared Atlas clusters, and later cover the transition to production, focusing on using dedicated search nodes to enhance performance.

If your GenAI app is built on MongoDB, chances are you're taking advantage of Atlas Vector Search.

Even if you aren't yet, now is a great time to learn some best practices when working with Atlas Vector Search to enhance the performance of your application.

We'll walk through some tips on how to avoid potential issues and make the most out of the functionality.

At this point in your learning journey, you'll be ready to put your new skills to the test. To earn your badge, simply complete the content in the learning path and then take the short test at the end. After passing the test, you'll receive an official Credly badge via the email you provided. Be sure to share your badge on LinkedIn to show off your new skills. So are you ready to fine tune your GenAI app and bring it to life for real world users? Let's get started and turn your innovation into impact.