digiLab Academy: “AI in the Wild: Foundations in Machine Learning for Future Flight"

digiLab 学院：“野外人工智能：未来飞行的机器学习基础”

• 批准号: 10064441
• 金额: $ 6.37万
• 依托单位: DIGILAB SOLUTIONS LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10064441
• 关键词: digiLab; Academy; AI; Wild; Foundations

**Upskilling Future Flight Engineers and Analysts**We are building a 3-month, part-time course which will upskill junior Future Flight engineers and analysts in their workplace. It's called "AI in the Wild: Foundations in Machine Learning for Future Flight". These engineers/analysts typically possess domain-specific knowledge about their systems and familiarity with their data. But the national AI/ML skills gap means that over 90% of data isn't even being used, and valuable insights are being missed. digiLab wants to change this.**Course Structure**Each month will include three weeks of lectures, practice exercises, and seminars; in the fourth week, we will deliver an in-person "hackathon" skills challenge, so that managers can see learning being put into action. We will also be keen to identify opportunities for further collaboration on Future Flight projects. Month 1 will teach Key Principles in ML; Month 2, Deep Learning; and Month 3, Probabilistic ML.**Learning Outcomes**It's called "AI in the Wild" for two reasons. Firstly, we want to empower learners to be able to tackle any problem independently, "in the wild': this will involve teaching not just how to use ML tools, but also how to approach new, unexpected, and varied data challenges. Secondly, through our extensive experience consulting for organisations operating in Future Flight sectors, we know that much of the data coming out of safety-critical environments or physically complex systems is "wild" - that is, messy or sparse. This could be due to malfunctioning sensors or an inability to acquire sufficient samples. So we will be teaching engineers how to reduce computational cost and increase confidence in their model outputs.**Upskilling Benefits**Upskilling employees increases productivity, retention, and wellbeing. Our course will accelerate business outcomes in Future Flight organisations and reduce their dependency on expensive external consultants to plug the in-house skills gap. Ultimately, the UK will benefit from the closing of the AI/ML skills gap and the acceleration of the Future Flight programme through the intelligent use of data.

**提高未来的飞行工程师和分析师**我们正在建立一个3个月的兼职课程，该课程将在他们的工作场所中提高小型初级飞行工程师和分析师。它被称为“野外AI：机器学习中的基础，未来飞行”。这些工程师/分析师通常具有有关其系统的特定领域知识以及对数据的熟悉。但是，国家AI/ML技能差距意味着超过90％的数据甚至没有被使用，并且遗漏了宝贵的见解。 Digilab想要改变这一点。**课程结构**每个月将包括三周的讲座，练习练习和研讨会；在第四周，我们将提出面对面的“黑客马拉松”技能挑战，以便经理可以看到学习被采取行动。我们还将渴望确定在未来飞行项目上进一步合作的机会。第1个月将在ML中教授关键原则；第2个月，深度学习；和第3个月，概率ml。**学习成果**它被称为“野外AI”，原因有两个。首先，我们希望授权学习者能够独立解决任何问题，“在野外”：这将不仅涉及教学如何使用ML工具，还涉及如何应对新，意外和多样化的数据挑战。其次，其次。通过我们对未来飞行领域运作的组织的丰富经验咨询，我们知道许多数据来自安全至关重要的环境或物理复杂的系统是“野性的” - 即凌乱或稀疏。或无法获取足够的样本。未来的飞行组织并减少对昂贵的外部顾问的依赖，以填补内部技能差距，英国将受益于AI/ML技能差距的结束和通过智能使用数据的加速。