Summary of Understanding the Skills Gap Between Higher Education and Industry in the Uk in Artificial Intelligence Sector, by Khushi Jaiswal et al.
Understanding the Skills Gap between Higher Education and Industry in the UK in Artificial Intelligence Sector
by Khushi Jaiswal, Ievgeniia Kuzminykh, Sanjay Modgil
First submitted to arxiv on: 20 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Machine learning educators can take note of a recent paper investigating how UK universities prepare students for jobs in the AI sector. The study compares university curricula with industry demands by reviewing course contents and job advertisements. By employing custom data scraping tools and Naive Bayes classifier analysis, the researchers identified 12 skill categories that employers value. While universities demonstrate a good balance of technical skills like programming and machine learning, they struggle to provide adequate training in data science and maths/statistics areas. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial Intelligence is revolutionizing how businesses operate, and as a result, there’s a growing need for professionals who can excel in this field. A new study examines how UK universities are preparing students for AI-related jobs. By analyzing university curricula and job ads, the researchers found a gap between what universities teach and what industries require. The paper highlights the importance of data science and maths/statistics skills that are often overlooked. |
Keywords
» Artificial intelligence » Machine learning » Naive bayes
