Register for free:

This Open edX meetup will highlight three presentations, covering data analytics, platform extensions, and methods for leveraging AI to simplify the process of content creation. 

The first presentation will be conducted by the Indian Institute of Management Bangalore, who will present an insightful overview of their data analysis experience utilizing Panorama Analytics within their professional programs on the Open edX Platform. This presentation will take attendees through the institution’s journey, from the initial implementation of analytics tools to the extraction of valuable, actionable insights that have significantly empowered their data-driven improvement processes. By sharing their comprehensive findings, the team aims to highlight the impact of detailed data analysis on enhancing the quality of online education, showcasing the ways in which data can inform strategic decisions and foster an environment of continuous learning and development.

The second presentation will be conducted by Shahidh K Muhammad, Co-Founder of Blend-ed and one of the founding engineers of Hasura, who  will share insights into the integration of Hasura’s open source GraphQL engine- with the Open edX Platform, highlighting its versatility and benefits for Micro Frontends (MFEs) and other development endeavors. Shahidh will demonstrate how Hasura can build and ship APIs and Apps really fast. Attendees can anticipate a deep dive into how Hasura’s capabilities can be used to extend the Open edX Platform features set by exposing the database over a secure GraphQL or REST API through configuration.

The third presentation will be presented by Amir Tadrisi, Founder of Cubite Technologies. They are working on an AI project to develop a RAG application to integrate it with the Open edX Platform for content creation. The POC is built on top of, ollama, and and langchain. The idea behind this work is to enhance the content creation for instructors using LLMs. How does it work? You can use any online or offline content,  pass it to the model, and instruct what type of learning content you want to create from it and the model provides the results. The difference between this implementation and tools like ChatGPT is that this model only uses the content provided for content creation. Multiple models can be used for different purposes, for example Llama for coding content and Mistral for other content.

Hope to see you there!