AI for Railways: Let machines learn for you
Artificial intelligence (AI) offers endless possibilities for rail companies in terms of using data more efficiently, refining processes and developing new business models.
- Get to know AI technologies, neural networks and examples for their usage
- Gain insights into example use cases of AI in the rail industry
- Learn the principle of machine learning and deep learning with the aid of prepared data
Rail infrastructures worldwide must be utilized better, whilst still fulfilling stringent quality requirements. This makes the use of artificial intelligence (AI) simply unavoidable. AI is the key factor when it comes to making the railway an even more attractive and efficient prospect. Over the coming years, elements of AI will be incorporated into practically every single digital process – e.g. for optimizing maintenance, damage detection and servicing work or for providing passengers with real-time information.
In this course you will familiarize yourself with current AI technologies and their impacts and limitations for railways. Examining example use cases from rail business, you will review and reflect on processes to classify and use data.
- Current state of technology and limitations of AI
- Impact on technology, work and society
- Difference between data science and artificial intelligence
- AI technologies, neural networks and examples for their usage
- Usage of neural networks to classify data
- The principle of machine learning and deep learning
- Case examples in the rail business
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