Course Structure

Our course is led by seasoned professionals with rich academic and applied research backgrounds, including members with hands-on LLM app development experience.

The curriculum goes beyond conventional AI studies to prioritize the development of real-time Retrieval Augmented Generation (RAG) applications—a foundational technique for leveraging Generative AI in practical settings. This focus addresses two prevalent industry challenges: applying Generative AI in production environments and crafting real-time solutions for industry use cases.

By the end of this program, you will have not only acquired the knowledge to create impactful, open-source LLM applications using RAG and live data streams but also completed a significant personal project. This opportunity allows students to dive deep into and excel in a technically demanding yet immensely rewarding emerging technological field.

💻 Course Format

In brief – it's primarily recorded. Designed with a blend of learning styles in mind, the course predominantly features pre-recorded lectures, enabling you to progress at their convenience. Moreover, interactive live sessions will be scheduled, and registered attendees will be informed beforehand. Thus, please ensure you've registered with an email address you access regularly and use for receiving calendar invites.

🗓️ Course Timelines

While the course is designed for flexibility, some modules may have recommended timelines to help you stay on track, especially before diving into the more complex RAG-specific and hands-on development modules. Registration remains open for the first 2 weeks as part of cohort-based version of the Bootcamp.

🎮 Course Completion Criteria

To complete the bootcamp, you must finish all quizzes by the established deadlines and submit your final project as part of cohort-based version of the Bootcamp. You have the option to work on the project either solo or in a team of two. If you decide to team up closer to the project submission, choose a partner with skills that complement yours, though you are equally encouraged to take on this challenge by yourself. In cases with a team of two, the prizes mentioned below will be awarded to both members.

Your project should involve creating and sharing an innovative GitHub project that utilizes the open-source RAG frameworks discussed in the coursework to tackle real-world challenges. More resources for bootcamp completion and eligibility for the top 6 teams will be discussed as the hands-on module approaches.

For self-paced learners, we are currently exploring ways to distribute certificates upon course completion. Stay tuned for updates on how you can showcase your accomplishments.

A Piece of Advice For those new to creating real-world AI applications, be ready to face challenges in selecting problems, integrating data, and applying foundational LLM knowledge. Engaging early is crucial to navigate these challenges successfully.