Predictive AI modelling with measurement data

Summary

Gain deep insights into building robust AI models, handling complex engineering datasets, and transforming traditional workflows into efficient, AI-driven processes.

The integration of artificial intelligence (AI) into engineering is revolutionising how we analyse data, make predictions, and optimise processes. However, harnessing AI's power in engineering applications requires a specific skill set, a comprehensive understanding of AI methodologies, and the ability to manage and interpret complex engineering datasets.

By attending this course, you will gain a comprehensive understanding of how to construct robust AI models, handle complex engineering datasets, and integrate these models into your engineering workflows. This course will empower you to improve your organisation's efficiency, decision-making, and innovation, enabling you to stay at the forefront of the rapidly evolving engineering landscape.

We recommend that you are proficient in Python programming to truly benefit from this course.

Who should attend?

Design or maintenance engineers, senior and principal engineers and technical leads who has responsibility for innovation and implementing improvement processes in the organisation. 

Please note:
We require delegates to bring to the course a laptop/device with Python 3.6 or later or Anaconda installed. We use git bash for code repositories and running commands.

Instructions for downloading this software for free will be included in the course joining instructions. It is the delegate's responsibility to ensure that they have access to the necessary software prior to arriving.

How will I benefit?

• Develop skills to manage and analyse complex engineering datasets.
• Gain proficiency in building, training, and validating AI models.
• Improve your understanding of the AI landscape within engineering applications
• Learn to interpret the results of AI models and communicate these insights effectively.
• Understand how to integrate AI solutions into existing engineering systems and workflows.
• Enhance your ability to manage AI projects from conception to deployment.
• Understand the ethical implications of AI and learn to develop and use AI models responsibly.
• Stay updated with the latest trends and advancements in AI.
• Improve your employability and open-up new career opportunities
• Increase your awareness of the ethical considerations surrounding AI
• Enhance your ability to scope AI projects
• Better identify the use-cases for AI in your engineering workflows
• Obtain comprehensive understanding of how AI works
• Learn how to build your own AI tools
• Improve your ability to communicate effectively with clients and stakeholders about AI
• Access to networking opportunities with other professionals interested in AI in engineering
• Access to expert instructors who can provide guidance and answer questions

Key topics

• Understanding the AI landscape within engineering applications
• Building and utilising own AI tools
• Ethical considerations in AI
• Scoping AI projects
• Identifying use-cases for utilising AI in engineering workflows
• Providing intuitive understanding of how AI works

Meet our trainers

These trainers regularly teach Predictive AI modelling with measurement data.