Data Science for Engineers
Manufacturers need to empower their engineers to make data & AI work
On-Demand Recording Now Available!
Data science and AI are game-changing technologies for engineering and manufacturing companies, but who is going to do all the data science?
At Altair, we envision a future where engineers are doing data science and taking daily data-driven decisions to transform their companies.
There are a plethora of applications for data science in manufacturing – from product design, supply chain optimization, fault prediction, preventative maintenance to demand forecasting and quality assurance. By bridging the gap between the data scientist and engineering roles – your organization can breakdown data silos and extract actionable insights to drive real business value.
The movement has just started. Watch the webinar on-demand to learn more.
- Learn what AI really means and how it can drive faster and smarter data-driven decisions that impact productivity, minimize risk and increase profitability
- Understand where the AI technology adoption in manufacturing stands today and why engineers are the key to unlock its potential
- Discover how low/no code is the future and why ‘Practical AI’ is needed to empower engineers to champion its success
Who Should Watch?
This webinar is perfect for engineering & manufacturing leaders of all levels, in particular:
- Production & Quality teams within Manufacturing Operations
- Engineering, CAE & R&D teams
- Manufacturing Operations – CTO / Digitalization Officer
- The CDO Circle – Chief Data Officers & Chief Analytics Officers
Anthony has been helping manufacturers all across Europe to revolutionize their businesses with game-changing technologies for over 15 years. He has a unique background in engineering and artificial intelligence, and has a passion to help customers drive business value with the latest technology. After working recently for a leader in the big data space, he has rejoined Altair to lead our Data & AI business in EMEA. He strongly believes that engineers will be the key to the adoption of AI in manufacturing.