Personalized course recommender for diverse skills and certifications

March 8th, 2023

This thesis topic would involve researching and developing a recommender system that can take into account users’ diverse skills and certifications, and provide personalized course recommendations that align with their career goals and interests. The thesis could explore different machine learning algorithms and data processing techniques to optimize the system’s accuracy and efficiency. It could also involve user testing and evaluation to assess the effectiveness and user satisfaction with the recommender system.

Thesis Type
  • Master
Presentation room
Seminar room I5 6202
Stefan Decker
Fateme Fathi

In our currently running project MyEduLife – The blockchain as a tool for decentralized storage of individual continuing education biographies, we focus on providing digital certificates of further education whose hashes are stored in a blockchain and on which the acquired skills and competencies are standardized and machine-readable.

With the abundance of online courses and learning resources available, it can be challenging for learners to identify the most suitable courses to meet their learning objectives. A personalized course selection and study planning recommender system can help learners select courses that align with their existing skills and certificates, and create study plans that optimize their learning experience.

This thesis aims to develop a recommender system for personalized course selection based on a user’s existing skills and certificates. The system will analyze a user’s skill set and certification history to suggest relevant courses and learning materials to achieve their learning objectives. The system will use machine learning algorithms to analyze user data and provide personalized course recommendations, taking into account the user’s learning preferences and previous course history. The proposed system will also include a user interface for course selection, allowing users to search and browse for courses and provide feedback on their experience. The effectiveness of the system will be evaluated through user testing and feedback, with the goal of providing a useful tool for learners to achieve their learning objectives efficiently and effectively.

  • Must:
    • Python
    • Docker, Kubernetes
    • Web technologies
  •  Beneficial:
    • Machine learning
    • Data analytics/visualization