| Name | Slack Account | |
|---|---|---|
| Nguyen Duc Chinh | [email protected] | [Nguyen Duc Chinh - TheFutureDev] |
| Dao Minh Dung | [email protected] | [Dao Minh Dung - TheFutureDev] |
| Nguyen Trong Hai | [email protected] | [Nguyen Trong Hai - TheFutureDev] |
| Phan Viet Hoang | [email protected] | [Phan Viet Hoang - TheFutureDev] |
| Nguyen Van Trinh | [email protected] | [Nguyen Van Trinh - TheFutureDev] |
Employees are facing issues in searching for suitable courses and building individualized learning paths, as well as creating a system where employees can track their skills and career goals.
- Our solution is an integrated platform, with automatic courses suggestion and learning paths construction from a wide variety of available and trusted sources, as well as a way to track the employees’ career development path and skills needed to achieve career goals. -The system automatically suggests learning pathways based on existing skills, specialized skills needed to develop, and personal targets.
Here is our demo for the AI system that we have built in the last two days
- First the training documents are processed (cleaning, tokenizing) then passed to an embedding model to get their representation vectors
- The acquired vectors are passed to a cluster model (Kmeans in this case), this will group our documents into sub classes which sharea common semantic and syntactic features
- The trained model (including tokenizer, clustering model, clustered training document) will be save into database for easy usage as well as inference speed
- User queries are processed exactly the same as in the case of training document to get their embeddings
- With a trained model from database, users will get the recommended course base on the context of their queries
- We plan to use state-of-the-art model in NLP for text encoder (transformer-based model)
- We are in lack of users' data and will collect more information from users to improve our model