Accurate data extraction from job offerings
An AI branch, NLP (Natural Language Processing) is used in education for pre-processing, analyzing, understanding and extracting data from various sources of data. Today, the application of NLP in education is diverse. It is being actively used in sentiment analysis in education, where learner feedback is crucial to assess the overall effectiveness of learning methods and techniques.
The Client is an accredited and licensed US online university. Its main objective is to provide affordable and high-quality education to people around the world. Being a next-generation university, the client puts innovations in education first. They wanted to transform education by offering both affordable and efficient education solutions for the remote education industry. They want their distance learning solutions to cover job skills most needed on the market.
The client was looking for a reliable NLP solution provider to bring more success to their business. They were facing the problem of job skill alignment in programs they create versus the current market demand.
The client needed a robust text analysis software to gain vivid insights from popular job listings. Our team has agreed to create an online academic advisor for learners that aims to analyze various job openings to identify the current and future career trends and market demand. Considering the benefits of NLP for education and learning and client’s goals set, we decided to stick to this technology.
The online academic advisor app extracts required metadata like language, soft and hard skills, education level or background from those openings with the help of NLP. The extracted data would help the client shape better online programs and courses catered to the learners’ needs and preferences.
Our team has developed a customized NLP application for education purposes from scratch.
The goals our team set:
We started with extracting job openings from various sources and developing an NLP model deriving skills from those openings. To train the model, we used extracted skills from a third-party provider.
At the same time, we were gathering data from multiple job search engines across the world, in order to create an accurate representation of the career trends and market demand. Then we linked them to university programs when the model was ready to be applied, like a bridge between the two. Then we moved to map job skills to course skills.
The InData Labs team has developed a robust mapping algorithm to link courses to job openings and identify the most popular courses among employers. This way we helped the client have a clear understanding of what’s their courses lack, so both learners and employers get what they need.
Another task was to create a learning path planner. Based on the data analysis results, we created a virtual online academic advisor that allowed learners to build specific learning paths within the university so that learners knew they were studying the skills needed by employers in the industry they choose.
The outcome of the work is an effective career student advisor solution designed to extract data from various online sources to build more relevant educational content.
The cooperation with InData Labs was fruitful in the following aspects: