Projects / Top Talent Project

Building a Personalized Recommendation System for E-Learning App

Application Deadline: February 22

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This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.

You can find our upcoming AI Innovation Challenges at

The problem

In an era where digital learning platforms are proliferating, the ability to stand out and retain users is increasingly tied to how well an app can cater to the unique learning needs and preferences of its users. Traditional, one-size-fits-all content delivery approaches fail to engage users at a personal level, leading to decreased app downloads, lower user retention rates, and ultimately, a diminished learning outcome. This lack of personalization can result in a disengaged user base, as content that does not align with an individual’s learning style, interests, or educational needs is less likely to be consumed and can contribute to user churn.

Impact of the Problem

On Users:

  • Decreased Engagement: Users faced with generic content that does not match their interests or learning objectives are less likely to engage deeply with the app, leading to superficial learning experiences.
  • Reduced Retention: The absence of personalized recommendations can lead to a higher churn rate, as users may quickly lose interest and seek alternative platforms that offer a more tailored learning experience.
  • Inefficient Learning: Without personalized content, users might spend more time sifting through irrelevant material, leading to inefficient learning processes and potential frustration.

On E-Learning Platforms:

  • Lower Downloads and User Growth: A lack of personalized experiences can deter new users from downloading the app, limiting the platform’s growth in a competitive market.
  • Diminished User Satisfaction: Generic content recommendations can lead to lower satisfaction rates, impacting the platform’s reputation and user reviews, which are crucial for attracting new users.
  • Challenges in Monetization: Engaging users with relevant content is key to unlocking premium features and subscriptions. Without personalization, platforms may struggle to convert free users into paying customers.

On the Educational Ecosystem:

  • Barrier to Educational Access: In the broader educational landscape, the failure to provide personalized learning experiences can exacerbate educational inequalities by not adequately serving users with diverse learning needs and backgrounds.
  • Stagnation in Educational Innovation: A lack of personalized recommendations may slow the pace of innovation within e-learning, as platforms remain focused on broad, generic content rather than developing novel, user-centric educational methodologies.

In response to these challenges, this project aims to revolutionize a learning app by integrating an AI-driven personalized recommendation system. Utilizing advanced technologies, the project seeks to create a dynamic, engaging user experience by offering content recommendations that are meticulously tailored to each user’s preferences, learning objectives, and behavior patterns. By doing so, the initiative not only aims to boost app downloads and user retention but also to contribute positively to the educational outcomes of its users, setting a new standard for personalized learning in the digital age. This approach addresses the critical need for customization in educational content delivery, promising a more engaging, efficient, and satisfying learning journey for users across the spectrum.

The project goals

The overarching goal of this initiative is to enhance the e-learning experience through the development of a personalized recommendation system within a six-week timeframe. This endeavor is pivotal for demonstrating the system’s potential to revolutionize content delivery in educational apps. The project is structured around several key objectives:

  • Data Collection and Preparation: Collaborating closely with our partner, we will access and refine their user data, ensuring it is optimally cleaned and structured for in-depth analysis. 
  • User Segmentation with Machine Learning: The segmentation is based on a detailed examination of user behaviors, preferences, and demographics, enabling the delivery of highly personalized content recommendations.
  • Algorithm Development for Personalized Recommendations: The core of our project involves the creation of tailored recommendation algorithms. 
  • Advanced Data Analysis and Feature Engineering: By extracting and refining key data points, we aim to enhance the precision and relevance of our recommendation algorithms.
  • Implementing Real-Time Data Processing: To capture and act upon user interactions in the moment, we will implement a system capable of real-time data processing. 
  • Deployment of the Recommendation System: The culmination of our efforts will be the deployment of the recommendation system as an API endpoint on AWS, complete with thorough documentation for seamless integration with the partner’s app. 
  • Dashboard Development for Analytics: Develop a user-friendly analytics dashboard utilizing PowerBI.

By focusing on these objectives, we aim to deliver a Minimum Viable Product that not only demonstrates the transformative potential of our personalized recommendation system but also sets the foundation for further development and refinement. This project promises to elevate user engagement and retention for our partner’s learning app, marking a significant advancement in personalized digital education.

**More details will be shared with the designated team.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.

Find more information on how an Omdena Top Talent Program works

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities

Eligibility to join an Omdena Top Talent project

Finished at least one AI Innovation Challenge

Received a recommendation from the Omdena Core Team Member/ Project Owner (PO) is a plus

Skill requirements

Good English

Machine Learning Engineer

Experience working with Machine Learning and/or Data Analysis is a plus.

This challenge is hosted with our friends at

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