The demand of data skills in the Belgian job market is at historic highs due to the growing realization that data is an asset that can be turned into a competitive advantage. Companies that successfully integrate data, can reap benefits by making operations more efficient, by supporting better decision making and by freeing up workers from certain tasks. Yet there is a significant shortage of AI-skilled profiles, a gap that BeCode closes in a creative way.
Data science is on the rise. Harvard Business Review even labeled the role of a data scientist as the sexiest job of the 21st century as companies are starting to understand that these profiles can boost their businesses in many ways. But the barrier to enter the field remained high, with 42% of data science roles requiring a master’s degree or higher, according to Burning Glass. A gap that cannot be closed overnight.
Although data science and adjacent fields are often projected as theoretical and complex, the theoretical part is often half of what it takes to be a successful data practitioner. Let’s face it, theory does not tell you how to deal with messy business questions, unclean data, challenging deadlines, effective teamwork or stakeholder storytelling. And let this experience gap be precisely the reason why a large number of vacancies in the domain remain unfilled to this day.
We at BeCode therefore seek to tackle the experience gap at its roots by introducing a creative learning approach: active pedagogy. Next to learning about data science theory through hands-on projects, our juniors are, on a regular basis, challenged by industry experts such as Accenture, ML6 and KPMG to solve various data challenges. In this way, our juniors get a taste of what it takes to provide end-to-end solutions for applied data problems, straight picked from industry.
Humain’s AI Challenge
As Humain, an AI service company that focuses on designing, validating and executing digital innovation roadmaps, wanted to contribute to closing the digital skills gap, they offered our learners the unique opportunity of putting their knowledge to the test by letting them work on an enterprise business challenge. The goal? To build an end-to-end natural language processing (NLP) product that can extract data science business cases out of a collection of corporate documents.
Humain purposely framed a broad challenge, allowing learners to explore their creativity in the full end-to-end data science lifecycle. They stressed that a job as a data scientist is more than just model building. Successful data projects are built upon a good business case, effective data cleaning, emphatic storytelling, teamwork coordination, an explainable executive presentation, and so much more. After 10 days of hacking, the 5 BeCode teams came up with creative solutions such as:
- An AI use case extractor that tells you what AI technologies are relevant in your textual input.
- An interactive trend visualization tool that shows the difference in usage of AI technologies before and after Covid.
- An AI curated newsletter that sends you only relevant articles based on topics you care about.
- An industry categorization model that automatically organizes your documents by industry relevance
- A semantic search tool that helps you find relevant documents by incorporating knowledge about your function, industry and a description of what you are looking for.
Curious about Humain’s services? Don’t hesitate to reach out to them via LinkedIn.
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